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As part of our series detailing the use of AI in football , we have looked at the various ways sports organizations are deploying artificial intelligence to improve their performance both on and off the pitch. We have looked at some of the unique ways some of the biggest names in football are using AI in their own ways, from Arsenal’s in-house approach to United’s global partnerships. Here we will see how AI is being used to prevent injuries at some of football’s biggest clubs. How Bayern Munich Uses Artificial Intelligence The Bavarian juggernaut is nicknamed FC Hollywood for a reason. Bayern enjoy the lion's share of resources in the Bundesliga and have long been at the forefront of drives to modernize the game. They use artificial intelligence in many of the same ways as the other clubs discussed here, but they excel in one particular application of AI. Bayern Munich are arguably the leaders in terms of deploying AI to prevent injuries and maintain player health. Once again, the technologies are essentially the same as those mentioned above. Computer vision is used to ingest all sorts of game and training data, which is then analyzed by deep learning algorithms. Is a player favoring one foot over the other, or turning more slowly than usual? If so, then it might be time to give him a rest. Artificial intelligence can monitor player biometric data and warn the coaching staff when a player is running at a higher risk of injury than normal. This allows the club to prevent rather than heal injuries, protecting the club's most valuable assets. How PSG Uses Artificial Intelligence One way that PSG uses AI differently to other clubs is their use of "wearables" to gather player data. As we have spoken about previously, ultimately the key differentiator for artificial intelligence technologies will be access to data . PSG see data coming from player-worn devices as key to better understanding their risk of injury. Of course, the Parisian giants use artificial intelligence in many of the same ways as the other clubs. However, as the use of AI proliferates and first-mover advantages become eroded, how clubs use AI will be a more important factor than whether or not they use it at all. How Liverpool Uses Artificial Intelligence The storied English Premier League club have not revealed much about their use of artificial intelligence but they are known to deploy the technology to help prevent injuries. Similar to PSG, Liverpool leverage “wearables” data for measuring performance and output as a way to track player welfare. The club has partnered with Google DeepMind to enhance their data analytics and sports science ventures. As the club continues to enjoy the service of perceived older players, the 31 year old Mo Salah being a prime example, this approach appears to be paying dividends. How Manchester City Uses Artificial Intelligence Man City have undergone change like no other team in football over the last decade or so, both on and off the pitch It is true, of course, that the club’s success has come from massive investment from its generous owner, Sheikh Mansour. However, the club has invested incredibly well. While the hiring of the all-conquering manager Pep Guardiola or superstar Erling Haaland generates plenty of media interest, investment behind the scenes garners far less attention. One such area is the partnership with the multinational technology giant SAP . While SAP might be better known for supply chain management or CRM software, they are also global leaders in AI-driven sports analytics. Again, details are somewhat thin on the ground for exactly how City uses this technology, it is understood that the system offers real-time data analysis and insight into player fitness, fatigue, and potential injury risk. How AI Can Prevent Injuries in Football Artificial Intelligence is being deployed in every sport, from pickleball to the NFL and European football clubs are no different. The same technologies and data being used to improve training methods and decision-making can also help prevent injuries by better understanding player fitness and performance. Want to learn more? Click here to discover how clubs like Brentford use AI in their recruitment process or Real Madrid utilize artificial intelligence to improve their set-piece play.

The use of Artificial Intelligence is growing at an exponential rate and sports organizations are at the forefront of its practical application. From recruitment to injury prevention and game analysis, football teams are using AI to improve every aspect of their organization. Let's take a look at how some of the world's biggest football clubs are using artificial intelligence today. Click here to read our introduction to the use of artificial intelligence in sports analytics. How Arsenal Uses Artificial Intelligence Arsenal Football Club have long been synonymous with moves to modernize football and are often among the first clubs to adopt new training methods, player welfare systems and scouting models, so much so that Moneyball inspiration Billy Beane has been said to admire long-time Arsenal manager Arsene Wenger. As far back as 2012, Arsenal showed a keen interest in data science and the club bought a company called StatDNA . Arsenal are a notoriously private organisation so it is difficult to know exactly what StatDNA does for them. However, one of the company's few employees with a public profile has stated that she “hates passing percentage” as a metric, which is a typical Moneyball mindset, eschewing top-level statistics in favor of more insightful, harder-to-measure criteria. Although the specifics of StatDNA are proprietary we do know some things about the work they do for Arsenal. Through computer vision and deep learning algorithms, StatDNA requires about 20 hours to analyze a 90-minute football game. This is not because the software is slow, but because it takes in so much data from the game. It uses concepts like Tracking Data to assess the level of defensive pressure players were under during each passage of the game, how they responded to that pressure and what was the impact of that pressure. Another area that StatDNA assesses for Arsenal is the quality of actions recorded as part of Event Tracking . It is not all that useful to record the number of assists a player generates unless you can be confident that the passing player truly assisted the goalscorer. The obvious example is if the goalkeeper passes the ball to a center-back, who then dribbles the entire length of the pitch and scores a wondergoal into the top corner. The goalkeeper would be awarded an assist for this even though he played no part in the goal. This example is of course very stylized, but StatDNA does analyze many factors involved in an assist. For instance, they examine if an assist allowed the goalscorer to shoot with his favoured foot , or to shoot without breaking stride. They assess if the build-up play moved the goalkeeper out of position leaving the goalscorer with a bigger target. This information is hugely valuable at removing randomness or viewership bias from analysis and allows the club to make better-informed decisions. Arsenal uses this information to enhance their recruitment, training and performance analysis. It has allowed the club to improve its recruitment with diamond-in-the-rough singing like Gabriel Martinelli from the fourth tier of Brazilian football or William Saliba from France. How Manchester United Uses Artificial Intelligence Man United are one of the biggest sports organizations on the planet and it is no surprise they are looking to utilize artificial intelligence firms to improve their operations. Unlike Arsenal, they have not bought or developed in-house capabilities but rather the club is partnering with leading global AI providers. One of the primary partners in this effort is a company called Catapult Sports and their focus is on squad management. Squad management is an area of the game that United have historically excelled in. Legendary manager Alex Ferguson could build and manage title-winning squads year in, year out, and did it in an analogue world. Since his retirement he has talked with Havard about his season preparation and the result were plain to see in his relentless success. The game has changed somewhat since then and managers are happy to leverage AI to make this task easier. This is where Catapult comes in. Tony Strudwick , formerly the head of performance at Manchester United, who works closely with Catapult Sports, sums up this modernization of approach perfectly: “Any way of tracking performance through technology allows you to make smarter decisions and gives you an objective measure of performance. Twenty years ago we didn’t have the technology and you were reliant upon intuition alone and the coach’s eye." You can read the rest of his thoughts on the Catapult Sports website . Catapult Sports have partnered with over 3,000 football team around the globe and their data sets and network are unrivaled. Each club has adopted its own approach to AI, with Arsenal keeping it in-house and United partnering externally, but both clubs are leaning into this new era with enthusiasm. How Brentford FC Uses Artificial Intelligence Brentford is the pace-setter in terms of AI and data-driven recruitment policies. The London club is probably the most modern of all major football teams when it comes to data science thanks in no small part to their owner. Matthew Benham’s background was in sports betting before he moved into football ownership, and that is where he honed his data modeling and analysis skills. Benham's story is fascinating in its own right and for anyone with even a passing interest in football, recruitment, or even data science it is worth reading about how he revolutionized his club and football recruitment in general. Here we will look at some aspects of AI football analysis that Brentford does a little bit differently to everyone else. Where Brentford really come into their own is in terms of recruitment. As we mentioned above when looking at Arsenal, the real value of data and analysis often comes from doing things a little bit differently than everyone else. Assists are a commonly used metric but assists where the pass allows the goalscorer to shoot with his good foot without breaking stride is far more valuable. For recruitment of elite football talent, Brentford uses their own proprietary yardsticks for measuring players. Rather than analyzing players against the standard eleven positions on a football pitch, Brentford breaks their analysis down into 16 positions . Each position is evaluated against six criteria, which are not made public, and this is how the club asses its own squad and transfer targets. The club has a database of over 85,000 players globally and each player is assessed in either one or multiple positions. This AI-driven approach has allowed Brentford to recruit far more efficiently than other clubs and maintain top-flight status on a relatively small budget. They can unearth players in leagues many other clubs do not even consider, due to their data-driven AI-powered approach. How Barcelona Uses Artificial Intelligence Barcelona are one of the most iconic football clubs in the world and are known for their commitment to innovation. The club has embraced artificial intelligence, particularly for analyzing gameplay and developing strategies, as part of the club's leading program, The Barca Innovation Hub . As we have discussed previously , AI algorithms are particularly adept at analyzing vast quantities of difficult data. One such example is sifting through hundreds or thousands of hours of match footage to identify repeated patterns of play. This is one of the areas where Barca use AI the most. Computer vision is deployed to identify the repeated movement sequences and patterns that lead up to goal-scoring opportunities. Deep learning algorithms use both Tracking Data and Event Data to understand flowing moves and how direct actions, such as passes, and indirect actions, such as defensive pressure, combine into goals. Once identified, Barcelona can incorporate these patterns into their training regime. The same software is also used to better understand and prepare for opposition formations, tactics, and even set-piece play. There are far more formations and nuances to modern football than many pundits realize and the more complex a dataset the more useful AI technology becomes. There is even a very real chance that these AI technologies will identify patterns that the most advanced coaching minds may have failed to notice. Like most clubs Barcelona play their cards close to their chest but Kognia Sports is one of their artificial intelligence partners. Kogina is a global leader in the use of computer vision and deep learning algorithms to analyze football tactics. How Real Madrid Uses Artificial Intelligence Los Blancos are the biggest name in football so it should be no surprise to learn the club has invested heavily in artificial intelligence. One area that Real Madrid stands out in terms of their AI use is analyzing player decision-making. Using the same suite of tools as the other clubs on this list, particularly computer vision and deep learning algorithms, Madrid leverages AI to understand how players make decisions and what they can do to make better ones. The technology can track where a player looks prior to receiving the ball, his head movements, any changes in direction and ultimately asses if he made the best decision or not. It is possible that a coach could assess this intuitively over time, but it is not possible for a human or team of humans to do this at the speed or scale of AI. Remember, elite football clubs are using AI to track every action and movement of every player on the pitch in every moment of the game. Scanning and decision-making like this were long thought to be the reserve of the most elite players and with AI is it being digitalized. This means it can be understood faster and coached more easily and this could significantly change the game. Set-piece strategy is another area in which Madrid uses AI extensively. They use artificial intelligence to make decisions in everything from free kicks to corners. Should a player shoot directly at goal or pass the ball out wide? Against this particular opposition, is a corner better targeted at the near post or the far one? How far and aggressively will this keeper come out to catch a cross? These are all questions that AI is helping Real Madrid to answer more accurately and more quickly. How Football Teams Use Artificial Intelligence (AI) We have looked at the various ways some of the biggest clubs across Europe utilize AI in their operations, from recruitment and training to injury prevention and decision-making analysis. The use of these technologies in real-time has not yet been confirmed by these clubs that is certainly the direction the game is going. There is of course a long way to go but it is already clear that having an edge in the AI arms race can translate to on-field success in football. Will Arsenal's in-house approach win out over United's global partnership model? Will Bretnford's recruitment algorithms continue to find hidden gems and can Bayern's key players avoid injury more than their peers? Only time will tell, but we can confidently say that football teams that use AI will win out of those that do not. Click here to see how teams like Bayern Munich and PSG use artificial intelligence to manage player welfare and injury prevention.

Football is continually evolving and is now at the forefront of the use of AI in sports. From talent recruitment to injury prevention, and in-game decision-making to set-piece routines, AI is revolutionizing football . The biggest clubs across Europe have incorporated artificial intelligence into every aspect of their operations. Here we look at eight AI quotes from some of the greatest names in football. "Football is not artificial intelligence.” Manchester City manager Pep Guardiola has a reputation for making tongue-in-cheek comments during interviews and this looks like one such remark. Despite making the bold remark against AI, his employer and Manchester City owner City Football Group have just hired Laurie Shaw, an astrophysicist, as their Lead Artificial Intelligence Specialist . City have hired four such AI specialists, so despite what Guardiola may say publicly, the club are leaning into the AI revolution heavily. “In 10-15 years, it will not necessarily be a football specialist who will be a manager for a club. It will be management specialists rather than football specialists, because the football decisions will be made by technology.” Arsène Wenger , the legendary manager of Arsenal Football Club, has long been a revolutionary figure within the world of football. Currently the Chief of Global Football Development for FIFA, Wenger has strong opinions on how far the application of Artificial Intelligence in sports will go. “When you play 50 or 60 games a year - for a club like Manchester United for example - if you’re [going to be] successful, how you manage your squad is so important.” Tony Strudwick, former head of performance at Manchester United, and now at Catapult Sports , is a global leader in sports applications of artificial intelligence. One area of focus for Strudwick is the use of artificial intelligence to manage player resources over the course of a season. This is something Manchester United have always been a leader in, from the analog methods of managers like Alex Ferguson and now with the help of artificial intelligence. "Data gives you the opportunity to be less biased in your decisions." "It’s not that data tells you who to pick, but data can tell you where to look," Rasmus Ankersen, Brentford's co-director of football, is a pioneering advocate for artificial intelligence and his club are at the forefront of the AI football revolution. Brentford have developed a reputation for finding hidden gems in the transfer market, allowing the club to compete far beyond its financial means. Ankersen talks about how data is key to any AI system, something we have looked at previously here . Brentford's Moneyball approach to football has seen the club become a Premier League regular and it all comes from innovative use of data . “Football is the most difficult sport to crack. There are 22 players who make 15-25 micro-decisions per second. Everything is related and it is a low-scoring game.” Giels Brouwer, Founder & CIO of SciSports , discussing the difficulties of advanced analytics in football. Football, despite being the world's most played and watched sport, is quite unusual from an analytical perspective. Scores are typically low and much of the action happens off the ball. SciSports groundbreaking machine learning algorithms to provide players, coaches and clubs with actionable insights. “Kogina provides me and my technical staff with essential information that helps me understand what is happening on the pitch and make the best decisions from the bench.“ Xavi Hernández is one of the greatest footballers of all time. He is also a founding investor in the artificial intelligence and sports analytics firm Kogina. As a player, Xavi epitomized intelligence and good decision-making and it is a real vote of confidence in football AI for him to be among the early adopters. “Zone7 is the perfect partner to help us harmonize the data we’ve been collecting, optimize player performance, and lower injury incident rates.” Victor Orta is the Director of Football at Leeds United and he is another football executive who has seen the benefits artificial intelligence can bring to the game. By monitoring all aspects of player performance AI can identify risk patterns that lead to injury and produce real-time injury threat alerts. This is estimated to reduce player injury incidence rates by 50%. “The insights produced are widely used across our football operations – in scouting and talent identification, in game preparation, in post-match analysis, and in gaining tactical insights.” Ivan Gazidis is one of the top executives in world football and is currently the Chief Executive of the storied Italian club A.C. Milan. The South African-born businessman is an Oxford graduate and a long-term believer in the use of artificial intelligence in football . As discussed previously on Aiifi , artificial intelligence is revolutionizing every aspect of modern football and Gazidis calls out both on and off-field aspects of the sport. Quotes About AI in Football Some of the best minds in football are working to apply AI to the sport and these quotes give us a glimpse into how they are going about it. Artificial intelligence is changing how football clubs recruit, train, play, and even protect their players. If you enjoyed these quotes why not read some of our other collections of quotes from the likes of Geoffrey Hinton and Demis Hassabis .

Football is struggling this season with controversial VAR calls that range from the confusing to the outright incorrect. This has seen coaches come out and claim the technology is not up to scratch, fan outrage, and even calls for games to be replayed. So what has gone wrong and how can artificial intelligence help? What is VAR? VAR is an acronym for Video Assistant Referee and it is a suite of software used in football leagues around the world to help the on-pitch referee. VAR is managed on a game-by-game basis by additional support referees. It is used to overturn “clear and obvious errors” by the referee during the game, to review offside and handball decisions with the aide of slow-motion replays, and to notify the referee of any incident he may have missed. How Does VAR Work? Although there is still a significant human element to VAR, some parts are based on software particularly when analyzing offside decisions. The essence of an offside call is to determine if one player is more advanced than another at a given moment. In a fast-moving sport like football, this is obviously very difficult. VAR has implemented a process of “drawing lines” on the pitch to determine which player is more advanced. VAR And The Offside Rule A player is in an offside position if any part of the head, body or feet is in the opponents’ half (excluding the halfway line) and any part of the head, body or feet is nearer to the opponents’ goal line than both the ball and the second-last opponent. If both of these conditions are met then a player is offside. This becomes an offence when a player in an offside position at the moment the ball is played or touched by a team-mate and then becomes involved in active play. If this rule sounds very technical, that’s because it is. Many aspects of the offside rule are regularly discussed and argued by football fans but two key components are relevant to VAR. Firstly, how is the exact moment of the ball being passed decided? And secondly, how is “nearer to the goal” measured? Unfortunately despite some significant technological advancements, these two steps are manually completed by hand. Could AI Help With VAR Offside Decisions? As you can see in the video, the lines are drawn at the single-pixel level, manually , by a human relying on their own eye. Although VAR gets the vast majority of these calls correct, the consequences of an incorrect decision can be season-defining. Computer Vision and VAR Computer Vision is a branch of artificial intelligence that converts camera feeds into analyzable data. The VAR system already relies on well-established Hawk-Eye computer vision technologies to c alibrate the camerras prior to the game. However, despite this use of computer vision, offside decisions are still made by hand. Computer vision is already used extensively to analyse player movement in football and it should certainly be considered for use by VAR. Wearable Devices and Audio AI Wearables are a relatively new field of AI that could assist referees and VAR. The wearing of highly advanced football boots with tracking devices has recently been approved by the Premier League . The purpose is for more general data gathering and analysis but it is not much of a leap to see it incorporated into the offside check process. Another area of AI that could assist VAR in making offside decisions is the advancement of audio signal processing algorithms. It is essentially the aural version of computer vision, and software such as SoundSee can ingest audio feeds, convert it to analyzable data, run machine learning algorithms and produce usable insights from the sounds. Will Artificial Intelligence Fix VAR And Refereeing? FIFA have already begun testing the use of AI in refereeing but there is a long way to go. As artificial intelligence becomes more mainstream over the coming years it will almost certainly be incorporated into football referring and VAR. However, that does not mean AI will replace human referees . There is a famous quote from Rob Thomas about AI (that you can read here ), that can be easily adapted to the application of AI in football refereeing: AI is not going to replace referees, but referees who use AI will replace the referees who do not.

The AI landscape is continuously, and rapidly, changing. New technologies pop up and disappear all the time. Sources of data are discovered and shut down on a regular basis. Billions of dollars are invested in start-ups, and thousands of job losses are announced seemingly every day. It can be difficult to keep up with all the changes (although following Aiifi is a good start!) but some changes deserve more attention than others. One such example is the recent announcements impacting the legal environment surrounding artificial intelligence. Safe, Secure, and Trustworthy AI On October 30th US President Joe Biden announced a sweeping Executive Order on Safe, Secure, and Trustworthy Artificial Intelligence. The goal is to promote the safe development and use of AI that is in the “interests of the American people.” That is a very broad aim and there are obvious questions about how it will work in practice. The AI Bletcherly Accord Meanwhile, UK Prime Minister Rishi Sunak hosted an AI summit, bringing together industry leaders and government officials to discuss the potential of catastrophic harm to humanity from AI. This led to the signing of “ the Bletcherly Accord ” bringing the world’s superpowers into alignment on how to control and monitor “frontier AI”. The EU View on AI Law The EU, not wanting to be left behind in this race to legislate, is looking to bring in sweeping new laws to ensure AI is overseen by people, and not automated systems, to prevent harmful outcomes . Although the European Parliament first introduced AI legislation in 2021 that was essentially a framework for identifying and classifying AI. At the time of writing, there are no EU laws to control the development or use of artificial intelligence. Rather the first push is to register AI and ensure it follows existing legal frameworks within the bloc. Why Legislate Artificial Intelligence So what does all this mean? In truth, it will probably do very little to change the trajectory of artificial intelligence. Business interests have long been happy to skirt their own governments by moving production offshore to lower-legislation locations, utilizing complex legal structures to avail of tax havens or just outright cheating the system. Why then are governments across the globe rushing to legislate AI? There are likely many answers to that question but one thing is certainly true. The threat from “ runaway AI ” is very real. While the public focus of AI has been on generative AI such as ChatGPT and potential job losses, many other applications are far more worrisome. Nefarious actors might use AI to develop biological weapons beyond our current ability to defend against them. Much of our strategic infrastructure (think power grids, air traffic control, and telecommunication networks) runs on software. Where we celebrate the application of AI in these are with developments such as self-mending networks, we are equally vulnerable to autonomous AI designed to attack this same infrastructure. Why Current AI Legislation Will Fail These recent attempts by governments to protect society from harmful applications of AI are too little, too late. The advancements in AI in the last two years have been astounding and these moves are akin to closing the stable door after the horse has bolted. Even if requiring companies in Europe and the US to register their AI, authenticate it, and share it with government works for some companies, almost by definition, groups or individuals with bad intentions will simply ignore the law. Even well-intentioned developers will likely move offshore to avoid the red tape associated with these laws. The development of AI does not require laboratories, heavy equipment or hard-to-obtain supplies that have historically been simple to regulate. Anyone with a laptop and a rudimentary understanding of Python can leverage open-source libraries and build AI models from anywhere on the planet. Even if AI legislation were to succeed, exactly as intended, it would not necessarily be a good thing. One obvious concern is about stifling innovation. This applies to specific nations and humanity as a whole. If the US, for example, becomes a highly regulated jurisdiction for anyone looking to build artificial intelligence systems, the most likely outcome is that other countries become the global leaders in terms of AI development. Already, many Western countries lag behind the likes of Russia and China in terms of technology development. Would more legislation help in that regard? Moreover, some of the potential benefits of artificial intelligence are in hugely complex areas such as biotechnology and healthcare. Research in such fields often requires access to academic institutions, medical equipment and vast funding. This is something that would be much better served with a joined-up, cohesive, global approach. A nation-by-nation approach to legislation will almost certainly not help humanity achieve these AI benefits. How Can We Protect Ourselves From AI Rather than legislating the outcomes of AI, a more holistic approach is urgently needed to address all of the legitimate concerns around artificial intelligence. Can we build strategic infrastructure that is not so vulnerable to AI hacking? Can we de-digitalize some areas that are particularly vulnerable to attack? Whatever we do, to have any chance at preventing catastrophic outcomes a truly global response is needed. The USSR and USA were able to agree to nuclear non-proliferation during the height of the Cold War. A similar approach might be needed to protect humanity from some of the more extreme outcomes of AI. I have no doubt that artificial intelligence will benefit humanity in the long run, but executive orders and registration frameworks will do little to offset any of the downsides.

Google's new AI model, Gemini for Bard, is outperforming ChatGPT, posing a significant challenge to AI applications powered by OpenAI. Recent testing reveals Google's Gemini for Bard as a formidable AI model, surpassing ChatGPT 4 in 30 out of 32 logical tests across various subjects, including law, mathematics, physics, and ethics. This breakthrough could disrupt the AI market, raising concerns for AI companies reliant on GPT4. With Gemini for Bard on the horizon, businesses must adapt to stay competitive in the evolving AI landscape. Watch The Aiifi YouTube Short below for a quick summary: Read the summary of the video below: Recent testing has unveiled a significant development in the field of artificial intelligence, as Google's latest AI model, Gemini for Bard, emerges as a formidable competitor to OpenAI's ChatGPT 4. The results of extensive evaluations demonstrate that Gemini for Bard outperforms ChatGPT 4 in an impressive 30 out of 32 logical tests across a wide range of subjects, including law, mathematics, physics, and even ethics. Remarkably, in 90 percent of the test cases conducted, Gemini for Bard surpasses human performance. This revelation has sent shockwaves throughout the AI community, particularly among companies that rely on OpenAI's GPT4 to power their applications. The impending arrival of Google's Gemini for Bard has raised critical questions about the future competitiveness and viability of these AI applications. With the potential for Gemini for Bard to outshine existing AI models, businesses are now faced with the urgent need to adapt and innovate to stay relevant in this rapidly evolving AI landscape. The threat posed by Gemini for Bard extends not only to AI companies but also to various industries relying on AI-powered tools that produce text or image outputs. The question that arises is, why would the market choose an inferior product powered by GPT4 when a superior alternative backed by Google's Gemini is readily available? As the AI landscape continues to evolve , companies must navigate this new paradigm and explore strategies to remain competitive. Whether through collaboration with Google's Gemini for Bard or by enhancing their own AI offerings, businesses are compelled to adapt to this transformative shift, ensuring their continued relevance and success in the dynamic world of artificial intelligence. Keywords for SEO: Google Gemini, Bard AI model, OpenAI-powered applications, AI market disruption, ChatGPT, AI model comparison, AI landscape evolution, AI-powered tools.

Artificial intelligence (AI) is one of the most influential and disruptive technologies of our time. It is transforming every industry, every business, and every function. But what about the people who work in these organizations? How is AI affecting their experience as employees? In this article, Aiifi will explore how AI transforms employee experience in four key areas: recruitment, training, evaluation, and support. We will discuss the benefits and challenges of using AI for the employee experience and provide tips and best practices for employees and employers. Whether you are an employee looking to leverage AI for your career growth, or an employer looking to create a more engaging and productive workplace, this article is for you. What do we mean when we say AI and Employee Experience? Before diving into how AI is transforming the employee experience, let's first define what we mean by AI and employee experience. AI is a broad term that refers to the ability of machines to perform tasks that typically require human intelligence, such as reasoning, learning, decision-making, and natural language processing. AI can be applied to various domains and functions, such as healthcare, education, finance, marketing, and human resources. Employee experience, on the other hand, is a term that refers to the sum of all interactions that an employee has with their employer throughout their employment journey. Employee experience includes everything from recruitment to onboarding and training, performance evaluation and feedback, career development, and support. Employee experience influences employee engagement, satisfaction, retention, and productivity. Combining AI and Employee Experience AI and employee experience are essential for any organization's success in the digital age. AI can help improve the employee experience by automating mundane and repetitive tasks, providing personalized and adaptive learning opportunities, delivering timely and actionable feedback, and offering intelligent and proactive support. These benefits can lead to higher employee engagement, satisfaction, retention, and productivity, resulting in better business outcomes, such as increased revenue, customer loyalty, and innovation. However, AI can pose challenges and risks to the employee experience, such as ethical dilemmas, privacy concerns, skill gaps, and job displacement. These challenges require careful consideration and management by employees and employers, as well as clear communication and collaboration between them. In the following sections, we will explore how AI transforms the employee experience in four key areas: recruitment, training, evaluation, and support. We will provide examples of how leading organizations use AI in these areas and showcase some of the AI tools and software in use today. We will conclude with some tips and best practices Aiifi recommends for employees and employers to make the most of AI for the employee experience. 1 - Recruitment Recruitment is the first and most crucial touchpoint between employees and employers. It sets the tone for the rest of the employee experience and can make or break the employer's brand. However, recruitment is a time-consuming and costly process, especially when dealing with large volumes of applicants and high turnover rates. AI can help streamline and optimize the recruitment process, saving both parties time, money, and stress. The following 3 AI-powered solutions are great examples of how AI is being intelligently used in recruitment by leading organizations: Paradox: Paradox provides an AI-powered assistant for recruiters and job seekers. The assistant, Olivia, engages with candidates on web, mobile, and social channels to learn about their skills, expertise, and relevant job experience. Olivia then presents candidates with next steps, schedules interviews, and answers company- or process-related questions using natural language technology. Hirevue: Hirevue enables companies to deliver a more engaging candidate experience with conversational AI and automation capabilities. A recruiting assistant can hold text-based conversations with individuals, guiding them to the jobs that best fit their skill sets. In addition, Hirevue's AI recruiting assistant sends follow-up messages and updates candidate statuses to speed up the hiring process. iCIMS: iCIMS offers a talent acquisition platform that leverages AI and ML to help recruiters find and attract the best talent. The platform uses AI to analyze resumes, match candidates to jobs, rank applicants based on fit, and provide insights on talent pools and market trends. 2 - Training Training is another critical aspect of the employee experience that AI has influenced significantly over the last two years. Training helps employees acquire new skills and knowledge and improve their existing ones. As firms of all sizes will be acutely aware, traditional training methods can be costly, time-consuming, and ineffective, especially when dealing with diverse and distributed workforces in many companies post-pandemic. AI can provide personalized and adaptive learning experiences that cater to the needs and preferences of each employee. Here are some examples of how AI is being used in training by leading organizations: Docebo: Docebo is an AI-powered enterprise-level LMS used to educate and train employees across various industries. It offers AI-based personalized learning paths, content recommendations, and advanced analytics to improve employee training experiences. Apty: Apty is a digital adoption platform that provides in-app guidance, interactive flows, and personalized learning paths for employees. Companies use Apty to create custom training programs for their software and monitor employee progress as they proceed through these customized programs, making it a valuable AI-driven training tool. ProProfs: ProProfs is an online training software that offers course creation, assignment, and progress monitoring tools. They provide professional templates with drag-and-drop features that you can easily modify to your training needs. With AI-enabled features like gamification and personalized learning paths, ProProfs can enhance employee training experiences and improve skill development. 3 - Evaluation Evaluation helps employees receive feedback and recognition and measure and improve their performance. The limitations of traditional evaluation methods are that they can be subjective, biased, and inconsistent, especially when dealing with qualitative and behavioral aspects of work. AI can provide more transparent, accurate, and fair evaluation methods to enhance employee motivation and development. Here are some examples of how AI is being used in evaluation by some leading organizations: 15Five: 15Five is a continuous performance management software offering employee performance reviews and goal-tracking features. It helps managers and HR professionals to assess employee performance, gather feedback, and identify areas for growth and improvement. The AI-driven analytics identify trends and provide insights to optimize employee engagement and productivity that would not have been possible pre-AI. Reflektive: Reflektive is a performance management platform that streamlines employee evaluations, goal setting, and real-time feedback. With a focus on continuous improvement, this AI-powered tool offers customizable templates for performance reviews, one-on-one meetings, and goal tracking. The platform's analytics help managers understand employee performance, engagement, and growth opportunities. Lattice: Lattice is an employee performance and engagement management platform that facilitates goal setting, real-time feedback, and performance reviews. AI-driven analytics provide insights into employee performance, helping managers make data-driven decisions for employee development. Lattice also offers features like peer recognition, which fosters a positive work culture. 4 - Support Support is the final key aspect of the employee experience influenced by AI, which we will discuss in this article. Support helps employees access information and resources and receive assistance and guidance. However, traditional support methods can be slow, inefficient, and frustrating, especially when dealing with complex and urgent issues. AI can help provide intelligent and proactive support methods to improve employee productivity, collaboration, and well-being. Here are some examples of how AI is being used in support by some leading organizations: Capacity: Capacity is an AI-powered knowledge management platform that provides employees instant access to critical information. It acts as a central repository for company knowledge. It makes it easy for employees to find answers to their questions, reducing the time spent searching for information. Capacity was built from the ground up on AI, with machine learning and natural language processing powering their conversational AI helpdesk. Talla: Talla is an AI-powered intelligent assistant that automates routine tasks, answers employees' questions instantly, and streamlines workflows. It integrates with various communication platforms, including Slack and Microsoft Teams, making it easy for employees to get support without leaving their preferred tools. Lucy: Lucy is an AI-powered knowledge platform that searches and synthesizes data from various internal and external sources and provides concise answers to employees' questions. Lucy uses natural language generation to create summaries of millions of search results. It can join the conversation on communication channels such as Teams or Slack. Lucy eliminates the need for uploading data and ensures your employees always have access to the most up-to-date information. Conclusion: Embracing the AI-Powered Employee Experience As we have seen, AI will revolutionize the employee experience in recruitment, training, evaluation, and support. By leveraging AI, companies can create more efficient and effective processes, tailor experiences to individual employees, and foster a more engaged and productive workforce. However, employees and employers must approach the AI employee experience with a balanced perspective, proactively addressing the challenges and concerns. To make the most of the AI employee experience, Aiifi recommends the following: Employers Stay informed about the latest AI developments and applications in their industry. Invest in AI tools and platforms that align with their business objectives and employee experience goals. Work closely with their HR, IT, and data teams to ensure AI solutions are implemented ethically and responsibly. Communicate openly and honestly with employees about the benefits and challenges of AI, and provide opportunities for feedback and collaboration. Offer training and development programs to help employees upskill and adapt to the changing workplace landscape. Employees Stay curious and open-minded about the potential of AI to enhance their work and career. Take advantage of AI-powered tools and resources to improve their skills and performance. Engage in ongoing learning and development around AI to stay relevant and competitive in the job market. Be proactive in addressing any concerns or questions about AI and its impact on their role or workplace. Collaborate with their employer and colleagues to create an inclusive and empowering AI-driven work environment. The AI employee experience is not a futuristic concept but rather a reality already unfolding in many organizations worldwide today. It offers significant benefits, opportunities, challenges, and risks for both employees and employers. Aiifi expects more recruitment, training, and HR software to integrate AI capabilities into its offering throughout 2023 and beyond. Those who do not will get left behind in the marketplace as employers demand the best functionality in their tools. By understanding and embracing the AI employee experience, we can harness its power to create more engaging, fulfilling, and productive workplaces and ultimately drive better business results. The future of work is here, and AI plays a pivotal role in shaping it!

The real estate industry has always been one of the most dynamic industries in the world, constantly changing with the times. With the advent of artificial intelligence (AI), the industry will transform in the coming years. From agents and developers to appraisers, homeowners, buyers, property managers, and investors, AI in real estate is revolutionizing how we buy, sell, manage and invest. In 2023 and beyond, Aiifi expects AI to play an increasing role in the real estate industry, providing more accurate valuations, advanced property search engines, and even virtual tours of properties. In this article, we'll explore how AI is changing the game for all the different players involved in the real estate market. The future of real estate is here, and AI is leading the way. Real Estate Agents & Brokers Artificial intelligence is having a transformative role in the real estate industry, significantly impacting how real estate agents and brokers conduct their business. In 2023, AI real estate solutions have become indispensable assets for professionals in the field, streamlining various processes and enhancing the overall efficiency of transactions. Through machine learning algorithms, AI can analyze vast amounts of data to provide real estate companies with valuable insights into market trends, property valuations, and customer preferences previously unavailable. These new insights, in turn, allow agents and brokers to utilize AI technology to make well-informed decisions, offer personalized services, and, ultimately, close deals faster. It gives real estate agents using AI's ability a significant competitive advantage over those not using it. AI-driven chatbots and virtual assistants have revolutionized customer interactions at prominent real estate companies, providing instant, round-the-clock client support, thus significantly reducing response times and improving customer satisfaction. AI is being used to automate mundane tasks such as paperwork and administrative duties, freeing agents and brokers to focus on more critical aspects of their business. The integration of AI in real estate has also led to the rise of innovative technologies like virtual property tours, which enable potential buyers to explore properties remotely, further expediting the real estate transaction decision-making process. Home Buyers Artificial intelligence transforms home buying by providing buyers with more efficient, personalized, and data-driven solutions. One example is AI-powered property search engines like Zillow and Trulia, which use machine learning algorithms to analyze user preferences and recommend properties that best match their criteria. These platforms also predict the future value of properties based on historical data and market trends, helping buyers make more informed decisions. Additionally, AI-driven chatbots are increasingly used to streamline communication between buyers and real estate agents, making scheduling viewings and obtaining information about properties more convenient. The use of chatbots is resulting in much-improved customer service for prospective buyers who engage with real estate agents using AI. Virtual property tours have gained popularity. AI-powered platforms like Matterport allow buyers to virtually explore properties in 3D, saving time and reducing the need for physical viewings. Furthermore, AI has made the mortgage application process more efficient by automating income and credit analysis, making it easier for buyers to secure financing. Home Sellers Similar to buyers, the impact of AI on home sellers is significant, as it has introduced innovative tools and platforms that simplify and streamline the selling process. For instance, some home sellers are leveraging AI-powered chatbots to engage with potential buyers, answer questions, and schedule property viewings 24/7, ensuring higher responsiveness and convenience. Additionally, AI-driven platforms like Zillow and Redfin offer property valuation algorithms that help home sellers estimate their property's worth more accurately, allowing them to price their homes competitively. Another example is AI-powered virtual staging software, which lets home sellers digitally furnish and decorate their properties using 3D models. This software saves time and effort compared to traditional staging methods. It enables potential buyers to visualize themselves living in the space more effectively. Furthermore, AI-enhanced marketing tools, such as targeted social media ads and email campaigns, assist home sellers in reaching a broader audience and attracting the right buyers. AI-driven analytics are crucial in understanding buyer behavior and preferences, enabling home sellers to make data-driven decisions regarding property improvements and negotiations. Overall, AI is changing how home sellers approach the real estate market, providing them a competitive edge and ultimately helping them achieve better outcomes in their transactions. Real Estate Developers AI has increasingly transformed the real estate landscape, providing developers with a powerful tool to enhance efficiency and optimize decision-making processes. With the adoption of AI, both commercial and residential developers are leveraging advanced algorithms to analyze sizeable real estate data sets to identify trends, predict market fluctuations, and make informed decisions about the acquisition and development of properties. One notable example is AI-powered platforms like Enodo, which helps real estate professionals optimize their investments by providing valuable insights on rental prices, property prices, and potential investment returns. Similarly, technologies like Reonomy enable commercial developers to access property data and analytics, streamlining the process of identifying potential acquisition targets and assessing the viability of development projects. AI-driven property management solutions, such as SmartRent, are also on the rise, offering residential developers a means to automate various aspects of property management, from tenant screening to maintenance scheduling. Property Management and Maintenance AI significantly transforms Property Management and Maintenance companies by streamlining operations, enhancing tenant experience, and reducing costs. For instance, Zenplace, a property management platform, utilizes AI-powered chatbots to handle tenant inquiries and maintenance requests and schedule property showings, ensuring a seamless communication process. Another example is Facilio, which leverages AI and IoT to optimize building performance and automate preventive maintenance. By analyzing sensor data, Facilio's platform can predict equipment failures and schedule timely maintenance, reducing energy consumption and operational costs. Similarly, Verkada, a security solutions provider, employs AI-driven video analytics for property management companies to monitor building access, detect unusual activities, and enhance security measures. Furthermore, companies like Gridics use AI algorithms to analyze zoning codes and regulations, enabling property managers to identify potential violations and ensure compliance, thereby avoiding hefty fines. In addition, AI-powered platforms like NestEgg automate rent collection, expense tracking, and financial reporting, helping property managers save time and improve financial oversight. In the maintenance sector, companies like Augury and Uptake use AI-based predictive analytics to monitor equipment health in real-time, allowing property managers to address potential issues before they escalate into costly repairs. These AI applications streamline day-to-day property management tasks and create safer, more efficient, and more sustainable living environments. Appraisers & Valuers The impact of artificial intelligence on real estate appraisers is nothing short of revolutionary. Both commercial and residential appraisers benefit from AI-driven insights that help streamline their work and provide a more accurate, data-driven valuation. Tools like HouseCanary leverage machine learning algorithms to analyze vast amounts of data, including property features, neighborhood trends, and historical sales data. These tools enable appraisers to make more informed decisions when valuing properties, mitigating the risk of human error and reducing biases. In commercial real estate, AI-powered platforms such as Reonomy sift through complex data sets to provide appraisers with a comprehensive understanding of a property's value, considering factors like zoning regulations, income-generating potential, and occupancy rates. AI-powered appraisal tools have also paved the way for automated valuation models (AVMs), which use predictive analytics to estimate property values accurately. For example, Zillow's Zestimate algorithm, which combines tens of millions of data points, has become an invaluable resource for appraisers seeking to validate their assessments. By embracing AI-driven solutions, real estate appraisers can expedite the valuation process and improve accuracy, ultimately benefiting both buyers and sellers in the ever-evolving real estate landscape of 2023. Mortgage Lenders AI has significantly transformed the mortgage lending landscape, enabling greater efficiency, cost savings, and improved customer experiences. Quicken Loans, one of the largest mortgage lenders in the United States, utilizes AI-driven technology to streamline the loan approval process. Their system, Rocket Mortgage, uses algorithms to assess creditworthiness and verify income and assets, reducing the need for manual input and thereby accelerating the approval process. Another example is the UK-based start-up Molo Finance, which uses AI and automation to provide mortgage approvals within minutes instead of weeks. Their platform not only speeds up the process but also eliminates the need for intermediaries, thus reducing costs for both the lender and the borrower. AI has also paved the way for advanced risk assessment models, allowing mortgage lenders to make better-informed decisions. Companies like Zest AI utilize machine learning algorithms to analyze vast amounts of data, enabling lenders to predict loan defaults and mitigate risks. AI-driven chatbots and virtual assistants, like those employed by Bank of America and Wells Fargo, have revolutionized customer service in the mortgage lending industry. These tools offer instant support to potential borrowers, answering questions and guiding them through the complex mortgage application process, thus enhancing the overall customer experience. Real Estate Insurance AI is transforming real estate insurance firms' operations, streamlining processes, and improving risk assessment. Companies like Lemonade and Tractable utilize AI-powered algorithms to analyze and process insurance claims more efficiently, significantly reducing processing time and human error. By employing AI, these firms can also accurately predict and mitigate potential risks, leading to better underwriting and pricing strategies. Moreover, AI-powered chatbots have become an essential customer service tool, assisting policyholders with inquiries, and automating routine tasks, improving customer experiences and operational efficiency. Another notable example is Cape Analytics, which leverages AI to analyze aerial imagery and property data to assess property risks more accurately. This data-driven approach allows insurance firms better to understand a property's specific characteristics and surroundings, leading to more accurate pricing and risk management. Similarly, Zesty.ai harnesses AI to analyze billions of data points, including satellite images and weather patterns, to predict natural disaster risks, enabling insurers to create more resilient portfolios and offer better coverage to policyholders. Real Estate Investors Property valuation and investment analysis are significant examples of artificial intelligence impacting real estate investors. AI-powered platforms like Skyline AI and HouseCanary provide investors with more accurate and comprehensive property valuations by analyzing vast amounts of data, including historical transactions, neighborhood demographics, and local market trends. These platforms help investors identify undervalued properties, assess potential rental income, and make data-driven decisions on whether to buy, sell, or hold a property. In addition, AI-driven algorithms like those used by Reonomy enable investors to discover off-market deals and analyze property ownership data, allowing them to find potential real estate investments and opportunities before their competitors. Another prominent application of AI in real estate investing is in property management. Companies like Zenplace are leveraging AI-powered chatbots and virtual assistants to streamline communication between property managers, tenants, and maintenance staff, resulting in increased efficiency, reduced response times, and improved tenant satisfaction. Furthermore, AI-enhanced tools and platforms like Enodo assist investors in optimizing their property portfolios by recommending optimal rent prices and suggesting value-add renovations to maximize returns on investment. Overall, using artificial intelligence empowers real estate investors to make more informed and strategic decisions, leading to greater efficiencies, improved returns, and a competitive edge in the rapidly evolving real estate landscape. AI Tools and Software in Real Estate The real estate industry has witnessed a remarkable transformation by integrating top AI tools and software, streamlining various processes, and enhancing decision-making. Zillow's Zestimate leverages machine learning algorithms to provide accurate property value estimates. At the same time, tools like Restb.ai and Skyline AI enable automatic property image recognition and intelligent market analysis, respectively. Artificially intelligent chatbots, such as Holmes and Roof AI, enhance customer engagement and answer real-time queries, thereby improving real estate companies' lead generation and conversion rates. Additionally, AI-powered platforms like Cherre and Reonomy offer comprehensive data solutions for property investors, enabling them to make informed decisions by aggregating and analyzing vast amounts of data from multiple sources. Machine learning algorithms employed by companies like Proportunity and HouseCanary help predict property price trends and market fluctuations, thus empowering real estate professionals to make strategic investments. In property management, platforms like Zenplace and ManageCasa use AI to automate tedious tasks like tenant screening, the creation of property documents, and rent collection. Lastly, AI-driven virtual staging tools, such as roOomy and Virtual Staging Solutions, help create realistic, cost-effective virtual property tours, which enhance the overall user experience. These AI-driven innovations are revolutionizing the real estate industry in 2023, making it more efficient and customer-centric than ever before. Conclusion AI is revolutionizing how the real estate industry does business and transforming how we buy, sell, and manage properties. From agents and brokers to appraisers, homeowners, buyers, property managers, and investors, AI makes our lives easier and helps us make more informed decisions. Regarding real estate, AI is more than just a marketing gimmick; it's an opportunity for home sellers, real estate developers, and appraisers to improve and grow their businesses. AI is also a game changer for real estate professionals and can enhance the quality of life for future generations by making the mortgage and home buying processes more efficient, personalized, and data-driven. While AI has come a long way in the real estate industry and has many challenges ahead, it's starting to make its mark on the industry. AI is continuously being developed, improved, and implemented in new, innovative ways. Aiifi predicts that by the end of this decade, real estate professionals and the entire real estate market will look much different than they do now.

Have you ever struggled to take notes during a meeting, only to end up with a messy and incomplete document that doesn't capture the key points and action items? If so, you're not alone. Many people find note-taking a tedious and distracting task that takes away from their focus and participation in the meeting. Fortunately, there is a solution that can make note-taking more straightforward and more efficient: AI note-taking. AI note-taking uses machine learning algorithms and natural language processing techniques to streamline the note-taking process. AI note-taking apps, such as Otter, can automatically record, transcribe, summarize, and share your meeting notes accurately and quickly. In this blog post, we will explore how AI note-taking is transforming meetings, the benefits of using AI note-taking for meeting participants and organizers, and the best practices for using AI note-taking effectively. By the end of this post, you will better understand how AI note-taking can help you improve your productivity and performance in meetings. How Does an AI Note-Taking App Work? AI note-takers are tools that use artificial intelligence to capture and transcribe audio from all the meetings you attend and other voice conversations you have. They also provide additional features to enhance and organize the notes, which we detail below: Voice Recognition AI note-takers can recognize and convert speech to text accurately and quickly. They can also identify different speakers and label their dialogue accordingly. For example, if you are meeting with multiple people on Zoom, an AI note taker like Otter can record and transcribe the audio and show who said what in the notes. This can help you avoid confusion and miscommunication. Natural Language Processing AI note-takers can understand and analyze the meaning and context of the speech. They can also generate summaries, highlights, keywords, and timestamps for the notes. For example, if you are attending a webinar on a complex topic, an AI note taker like Fireflies can analyze and summarize the key points and insights from the speaker. This can help you understand and remember the information better. Handwriting Recognition Some AI note-takers can also recognize and convert handwritten notes to digital text. They can also sync the handwritten notes with the audio transcription and provide a searchable interface. For example, if you prefer to take notes by hand during a meeting, an AI note taker like Airgram can scan and digitize your handwritten notes and sync them with the audio transcription. This can help you access and search your notes easily. Slide Capture Some AI note-takers can also capture and insert slides shared during meetings into the notes. This provides a full context of the content that was discussed. For example, if someone presents slides during a meeting, an AI note taker like Hyperia can automatically capture and insert the slides into the notes. This can help you see the complete picture of what was discussed and how it relates to the slides. Integration AI note-takers can integrate with various apps and platforms, such as video conferencing, calendars, cloud storage, collaboration, CRM, and more. This allows users to record easily, access, share, and manage their notes across different devices and systems. For example, if you use Google Calendar to schedule your meetings, an AI note taker like Otter can automatically join and record your meetings on Zoom, Microsoft Teams, or Google Meet. You can also export your notes to Google Drive or other cloud storage services. Collaboration AI note-takers can also enable users to collaborate on their notes with others. Users can invite others to view or edit their notes online, add comments or feedback, assign tasks or action items, and track progress or updates. For example, if you want to share your notes with your co-workers or clients, an AI note taker like Fireflies can send your notes via email or messaging apps. You can invite others to view or edit your notes online, add comments or feedback, assign tasks or action items, and track progress or updates. These are some of the features of AI note-takers that can help users improve their productivity and performance in meetings. In the next paragraph, we will discuss some benefits of using AI note-takers for meetings. Benefits of using AI for Meeting Notes AI note-taking can offer many benefits for meeting participants and organizers: Improved engagement and active listening With AI note-taking, you don't have to worry about missing or forgetting important information. You can focus on the discussion and participate more actively without being distracted by typing or writing. You can also use voice commands to add comments, questions, or reminders to your AI-generated notes without interrupting the flow of the conversation. Enhanced recall and comprehension AI note-taking can help you remember and understand the key points and insights from the meeting. You can review your notes anytime, anywhere, and access features such as summaries, highlights, keywords, and timestamps. You can also search your notes by keywords, topics, speakers, or dates and find the information you need quickly and easily. Reduced stress and anxiety AI note-taking can reduce the stress and anxiety of taking notes manually. You don't have to worry about making mistakes, losing notes, or forgetting to follow up on action items. With a trusty AI assistant, you can trust that your notes are accurate, complete, and secure and that you have everything you need to succeed. Saved time and effort AI note-taking software can save you a lot of time and effort that you would otherwise spend manually taking notes. You don't have to spend hours transcribing, organizing, editing, or sharing your notes and meeting summaries. Let your AI meeting assistant do the work for you and focus on more important or creative tasks. Multisensory learning and accessibility AI note-taking can support different learning styles and preferences. You can choose how you want to consume your notes, whether by reading, listening, or watching. You can also use features such as captions, translations, or annotations to make your notes more accessible and inclusive. As you can see, AI note-taking can transform your meeting experience and help you achieve better outcomes. The following section will share some best practices for using AI note-taking effectively. Best Practices for AI Note-Taking for Meetings To get the most out of AI note-taking, you need to follow some best practices to ensure your notes' quality and effectiveness. Here are some tips to help you use AI note-taking tools successfully: Choose a reliable and user-friendly AI note-taking tool Many AI note-taking tools are available on the market, but not all are equally good. You must choose a tool that suits your needs, preferences, and budget. Some factors to consider are the tool's accuracy, speed, features, integrations, and security. For example, Otter is a popular and trusted tool that offers high-quality transcription, speaker identification, slide capture, summary generation, and more. Set up your device and microphone properly You need to set up your device and microphone properly to ensure that your AI note-taking tool can capture and transcribe your audio clearly and accurately. You must ensure your device has a stable internet connection, enough battery life, and enough storage space. You must also ensure that your microphone is positioned close to your mouth, away from any background noise or interference, and has a good volume level. Inform your meeting attendees about the AI note-taking process Before you start using an AI note-taking tool in a meeting, you need to inform your meeting attendees about it. You need to explain what the tool does, how it works, and why you use it. You must also get their consent and respect their privacy preferences, especially if you intend to record meetings. You can ask them if they are comfortable with being recorded and transcribed, if they want to opt-out or use a pseudonym, and if they want to access or edit their transcripts later. Review and edit your notes after the meeting After the meeting, you need to review and edit your notes to ensure they are accurate, complete, and organized. You can check for any errors or gaps in the transcription, add missing information or details, correct any spelling or grammar mistakes, and format your notes according to your style and preferences. You can also use features such as highlights, comments, keywords, and timestamps to enhance your notes and make them easier to understand and recall. Share and collaborate on your notes with others One of the benefits of using an AI note-taking tool is that you can easily share and collaborate on your notes with others. You can send your notes via email or messaging apps, export them to formats such as PDF or Word documents, or integrate them with other tools such as Google Drive or Slack. You can invite others to view or edit your notes online, add comments or feedback, assign tasks or action items, and track progress or updates. By following these best practices, you can make sure that you use AI note-taking tools effectively and efficiently. Now that you know how AI note-taking can transform your meeting experience, why not try it and see the difference yourself? Conclusion You've just learned how AI note-taking can transform your meetings from tedious and stressful to exciting and productive. You've discovered how AI note-taking can help you capture and remember every detail, insight, and action item from your meetings. You've also seen how AI note-taking tools, such as Otter, can make your note-taking process effortless and enjoyable with features such as voice recognition, speaker identification, slide capture, summary generation, and more. You've also received some valuable tips on how to set up, use, and share AI notes successfully. Now it's time to take action and experience the magic of AI note-taking. Don't let another meeting go by without using this amazing technology. Try AI note-taking today and see how it can improve your life. If you have any questions or feedback, please comment below. Thank you for reading, and happy note-taking!