Tag: AI

Artificial intelligence is rapidly becoming a fixture in the modern workplace, promising unprecedented efficiency and innovation. But as we delegate more routine tasks to algorithms, we face a critical question: Will genAI elevate our thinking and more deeply engage our key brain networks, or will it encourage us to default to cognitive shortcuts, effectively dampening our cognitive output? At NLI, we believe that as AI takes hold in organizations, the most effective teams will need to become more, not less, human in how they operate. This means doubling down on the unique skillsets of the human brain—our capacity for deep thought, critical thinking, creativity, and metacognition, or the awareness and regulation of one’s cognitive processes. AI can be a powerful partner, but only if we’re the ones making the decisions. Using it irresponsibly has the potential to cost your organization thousands, if not millions, in flawed strategies and missed opportunities. “Use It or Lose It”  Ensuring AI is a tool for better thinking begins by understanding what better thinking actually means for the brain. Key here is the principle of neuroplasticity— the brain’s ability to reorganize itself by forming new neural connections. The cognitive skills we engage in are the ones that strengthen, the ones we outsource, weaken. And as research begins to emerge from the academic labs, we can see early signs of this occurring when we rely on genAI. Studies show that improper use of generative AI has a dulling effect on our cognition. One landmark study, in particular, showed that when individuals used chatGPT for essay writing, over 80% of users remembered nothing of a topic they wrote about when they used the tool, compared to just 11% of those that wrote the essay without support. Furthermore, using GenAI as a replacement for critical thinking has been shown to produce generic, homogenous ideas – reduced variation in the ideas generated. Finally, studies have linked relying on genAI to eventual boredom and a reduction of intrinsic drive towards the work. Multiplied across an entire organization, poor GenAI habits risk coalescing into cultures of mediocrity and boredom. These studies also indicate the potential for a longer-term negative impact on brain structure itself, a neural atrophy often summarized by the neuroplasticity principle of “use it or lose it.” However, the solution isn’t to abandon AI, but to build out the skills needed to use it effectively. Here are three brain-based ways to ensure your team is using AI to enable, not inhibit, their thinking. Instill a culture of metacognitive thinking  Metacognition is the skill of stepping outside your own thought process to examine it – having an awareness and regulation of our own cognitive processes. When we engage in metacognition, we intentionally activate our prefrontal cortex, the brain’s executive center responsible for planning and self-awareness. Tip: Before turning to AI, consider why you’re facing a particular challenge, how you’ve tried to solve it in the past, and how you’ll think about any AI-generated output. Foster the habits of critical thinking While genAI models can process vast amounts of data, they don’t possess true understanding and self-regulation and motivation to solve the problem at hand. This requires critical thinking, an intrinsically human skill. People that think critically are motivated to find, reflect on and evaluate information from diverse sources in order to solve new problems, reach goals and learn. Leaders can help to foster these habits by both role modeling them and maintaining environments that are both psychologically safe and remain oriented towards a growth mindset. Tip: Treat AI outputs as a first draft, never a final product.  Hold space for creative moments. In order to maintain our ability to be creative, we may need to schedule time for it. That’s because creativity is enabled when your mind wanders. This allows the engagement of the brain’s creative networks, such as the default mode network. And while AI can serve as a useful tool to kickstart the creative process by generating initial concepts, it’s important to recognize that while these ideas can be helpful starting points, they may not be truly groundbreaking.  Tip: Structure your creative process into two distinct phases. First, use AI to generate a wide array of starting points. Then, walk away and allow your mind to wander. The rise of AI doesn’t diminish the need for human intelligence; it amplifies it. The critical question of how to use AI for better thinking is a central focus of the 2025 NeuroLeadership Institute Summit, Thrive Through Complexity.  In our final keynote session of the event, Using AI Toward Better Thinking, we’ll explore what better thinking actually means for the brain and how leaders can build the habits to use AI for this purpose. The path forward is clear: we must seize the opportunity to become more thoughtful, more creative, and more intentionally human. Register today for the 2025 NeuroLeadership Institute Summit: Thrive Through Complexity.

By Sinead Kinney, PHR and Rebecca Norberg, SHRM-CP It seems like everyone is talking about AI in hiring. You’ve seen the stats: nearly 70% of companies are expected to use AI in recruitment by the end of 2025. Why the massive AI adoption? Simple: AI solves fundamental human limitations in recruiting, especially when dealing with high-volume applications. But here’s the secret: merely using AI won’t guarantee you’ll get the right candidates. Are you even sure you’re sourcing the right candidates? In 2023, iTutor was on the hook for hundreds of thousands of dollars for age discrimination because their AI tool automatically rejected over 200 qualified women over 55 and men over 60.   To truly nail talent acquisition, you need a smart strategy that pairs AI’s muscle with disciplined human oversight and proven methods for checking our own unconscious biases. Think of it as a dynamic duo: AI handles the heavy lifting, streamlining and automating tasks at speed, while acting as a thought partner for the human who knows how to wield its power and verify its accuracy. In turn this frees up precious time and energy for tasks requiring human thought, creativity, diligence and experience. The pair? Unstoppable. Separate? Flawed and fallible. Talent acquisition on AI autopilot  Right now, most organizations are using AI to automate and sort through applications, cover letters, emails, and job boards all while thinking they are finding qualified candidates, making data-driven decisions, and managing massive applicant pools. AI does an amazing job during these first levels of the funnel, but still requires a human to review and make decisions.  Zeroing in on top talent AI tools are fantastic at cutting through the noise. AI-driven sourcing and matching systems can instantly scan hundreds of millions of professional profiles, analyzing job requirements against skills, qualifications, and experience. Your recruiting team doesn’t have to waste time manually scouring job boards; instead, they get a ranked list of top candidates prioritized by how well they match the must-have and nice-to-have criteria. This frees them up to focus on what truly drives success: communicating and building relationships with those candidates. Boosting quality and catching misrepresentation AI doesn’t just speed things up; it improves the quality of the candidates who move forward. Research shows that the use of an AI-assisted pipeline resulted in a 20% increase in the pass rate for final-stage human interviews, proving AI identifies higher-quality talent. Even better, AI helps detect the widespread problem of skill inflation (or lying on a resume).  In 2025, BetterHealth found that 78% of job seekers have considered misrepresenting their resumes, and Business News Daily reported that  60% have admitted to actually lying about their proficiency in skills they did not have. By implementing conversational AI assessments organizations can identify the roughly one in five candidates who claim technical skills they cannot actually demonstrate.  Data-driven decisions Forget guessing. Predictive analytics is the ultimate tool for evidence-based hiring. It analyzes patterns from your most successful current employees to forecast future needs and pinpoint characteristics correlated with high performance. This strategic approach provides objective data points that complement human evaluation, moving beyond intuition or gut feelings. Plus, by focusing on skills and objective indicators, AI helps mitigate unconscious bias and aids in increasing diversity by widening the talent pool.  With 70% of candidates using AI to apply for jobs (for everything from matching their resumes to skill requirements on job postings, completing applications, to even answering questions during interviews), organizations need to be smarter, faster in order to stay ahead. Breaking the cycle of bias, the first step is awareness  In AI, bias is defined as a systematic error in judgements, which can develop in AI systems due to the humans inputting and training the algorithm. Then as humans and AI continue to interact without this understanding, they create an echo chamber, which can magnify their biases. Our brains are hardwired with unconscious biases, the NeuroLeadership Institute (NLI)’s SEEDS Model® refers to these as Similarity, Expedience, Experience, Distance, and Safety biases. Similarity Bias – our brain’s preference for people who are similar to us or share common goals, like opting for a candidate that graduated from our alma mater. Expedience Bias – our brain’s way to conserve energy by relying on mental shortcuts based on intuition or limited information, like discarding resumes missing a college degree when it may not be a bona fide occupational requirement. Experience Bias – our brain’s assumption that our perceptions are an accurate, objective representation of reality, like restricting your talent pool to those who have worked within a particular industry. Distance Bias – our brain’s natural tendency to overvalue things that are near in physical proximity, time, or responsibility, like preference for the most recent candidate you interviewed even if they weren’t the most qualified. Safety Bias – our brain’s way of protecting against the unknown which is viewed as inherently riskier than the known, like not choosing to make an offer to a candidate because they “aren’t a culture fit.” Now that we can recognize the cycle of bias, we can partner with AI leveraging each other’s strengths, while mitigating our weaknesses.  Let’s explore what happens when we combine this awareness, The Neuroscience of Better Hiring® (NLI’s SELECT product), and AI’s processing power. The human touch—mastering bias mitigation to flip the script on AI in talent acquisition AI may handle the data, but ultimately humans make the final decision. That means we must actively guard against the biases hardwired into our brains. This is where NLI’s SELECT core habits come into play: Embrace the evidence, Follow a process, Challenge your thinking. Anchoring on the SEEDS model, they help recruiters and hiring managers interrupt and redirect thinking by breaking bias mitigation into habits to make better decisions. These can be super charged with the help of NILES, our Neuro Intelligent Enhancing System. NILES isn’t your standard GenAI. With expertise from over 200 PhD scientists and subject matter experts, and nearly three decades of business practice with Fortune 100

By Dr. David Rock Offers for digital, AI-powered coaching are starting to pop up in the inboxes of HR leaders everywhere, with lots of promises of cost savings for coaching. But how do you tell real from vaporware? Let’s admit this is a bit of a brave new world, sometimes exciting and sometimes terrifying. Even more so if you’re a decision-maker in an organization who’s expected to find a coaching AI that’s “best in show” for your organization and that’s going to “talk” to huge numbers of important people in your firm. This needs to be done responsibly, and not just be based on whizz bang tech, or how nice the salesperson was to you. There’s a certain “fit for purpose” issue to be clear about here. If you just want a digital coach to help people set goals and turn them into steps, there are dozens of options to choose from, many of them now quite low cost. However, the true value of coaching is not just goal setting — it’s making smart people smarter, efficiently. Doing this requires a more sophisticated tool than just a goal-setting coach.  The question here is, how do we measure this? How, as a responsible purchaser of AI, can you know you are getting the best possible solution available? The answer should not just be about the technical bells and whistles. In a short time, all AI coaches will be able to be integrated into any platform, have great dashboards, speak all languages, and be compliant with all the technology needs of your firm.  We believe there is one truly responsible way to differentiate the options. That is to do what we all do with other new technologies: speed test them. Only in this case, instead of actual processing speed, the test is to see how many people find true value in their coaching conversations with their AI coach. Not just that they liked the conversation, but that it significantly improved their situation or helped them solve their core challenge. We’re ready to throw down the gauntlet: We believe we have the smartest, most effective AI for managers and leaders, because we’ve been working on this challenge not for two years with a team of fresh-faced engineers, but for 26 years with a massive global community of cognitive scientists and business leaders. Our tech is not necessarily better or worse than anyone else’s, but the effectiveness of our coaching conversations is off the charts.  How do we know? Our AI is creating breakthrough insights that drive real change, in four out of five conversations, and faster, making it more likely for people to take action and in less time. Don’t believe us? Put us to the test. Book a demo of NILES to see it in action.  After all, if you’re going to give hundreds of thousands of managers someone to talk to, you should want those conversations to be as useful as humanly, or in this case digitally, possible. 

By Chris Weller With the rapid pace of technological change — artificial intelligence, in particular — it can feel like the world is a little less recognizable with each passing day.  It’s up to leaders to help their teams respond to these changes, offering new skills and systems that make workforces more adaptable and resilient, rather than overwhelmed and stuck. Join us at the 2025 NeuroLeadership Summit, where leading scientists and industry practitioners converge to share best practices, new ideas, and helpful strategies for thriving through complexity. On November 12-13, this virtual global event will offer insight into the most critical issues facing leaders today: Upholding accountability amidst constant change. Building new and better habits at scale. Collaborating with AI to enhance — not dull — human thinking. Evolving DEI strategy within organizations. Here’s a handful of session previews to see firsthand what to expect at this year’s NeuroLeadership Summit. Register now to secure your tickets, as spots are selling fast. Registration includes full virtual access to both days of the 2025 NeuroLeadership Summit and on-demand recordings of all sessions. NLI Corporate Members receive additional discounts and benefits.  Leadership Today: Thrive Through Complexity By most estimates, change is accelerating year over year. New technologies, systems, strategies, and expectations are replacing existing ways of working in what feels like real time — and it’s all happening faster and faster. Stretched thin and wary of the next shift, what is a burned-out organization to do? This session will explore the challenges leaders and their teams face from a cognitive perspective. What factors weigh most heavily on people? What have we learned in the last decade that can serve us now? How is AI helping or hurting these working conditions? And perhaps most importantly, what can be done to ensure teams can thrive through all this complexity?    What Will Leadership Look Like In 5 Years? As AI becomes everyone’s coworker, it’s essential that leaders upskill their teams to handle AI-assisted tasks. That means helping people move from one end of the AI fluency spectrum to the other — from AI resistors and the AI ambivalent to AI users and AI fluent. Without a solid foundation for how to work with AI, teams risk outsourcing their thinking to the platforms that have been shown to dull our cognition when it should be enhancing it. Attendees of this session will also hear from world-class practitioners who have been using proprietary AI at work and studying its effects. The resulting picture will be a window into the future: how leaders should be thinking about the changing nature of their roles based on the uncertainties of modern work. Toward a Real Science of Habit Activation at Scale When your brain is so stressed it feels like it’s on fire, what are the habits you and your team default to? The answer to that question will tell you what kind of culture you’re building in high-stakes, high-pressure moments — much like those we’re facing today. This session focuses on the science of behavior change across an organization. It introduces core principles from research around social learning, the right way to build habits, at scale, and how AI can help facilitate shared behavior change as well as sustainment. Using AI Towards Better Thinking As generative AI platforms proliferate, we must remain cautious not to hand over the keys to our thinking. GenAI is still prone to mistakes, hallucinations, and bias. Research is also showing that asking GenAI for answers can make us less creative and worse critical thinkers. The trick, as AI makes its way into the workplace, is to use the technology in ways that enhance thinking. That’s what this session will teach attendees. We will explore the science of cognition to explain why AI is so tempting but ultimately a poor substitute for real thought, and introduce key habits that every leader should be focusing on to make sure AI amplifies human cognition and helps teams produce their best results.   Register now to secure your tickets, as spots are selling fast. Registration includes full virtual access to both days of the 2025 NeuroLeadership Summit and on-demand recordings of all sessions. NLI Corporate Members receive additional discounts and benefits. 

By Dr. David Rock Right now, around 1% of managers and leaders in organizations get high quality coaching each year. We believe that number should be 100%, and that AI can get us there.  Yet, for this to become a reality, an AI coach can’t just be there to help you set goals or ask Socratic questions. It needs to be a highly sophisticated system that truly understands humans and human learning, and interacts with people in ways that make them better leaders.  To be clear – this is not the path that the big GenAI providers are on, where the race is on to be the tool that provides answers as fast as possible. For some of us, this feels reminiscent of the search wars, when Google  competed with firms that few young people have heard of, including AltaVista, Lycos, Excite, infoseek and Hotbot. Google won that war by shaving seconds and then milliseconds off of search times. When you’re hungry, a couple fewer seconds for your AI to find you the tastiest thin crust pizza within a 10-minute drive might be compelling, and there’s definitely a role for an AI that focuses on speed in answering everyday or technical questions. However, when it comes to helping managers and leaders be more effective at understanding, motivating and developing their teams, simply giving these folks a quick answer might not do the trick. At the NeuroLeadership Institute, we believe that the best AI tools for managers and leaders will actually be like great leaders themselves. Not just providing answers all the time, but helping people think better for themselves. Both role modelling great leadership, and helping people get smarter at the same time. Think of this as a whole different type of AI. An AI built on a different set of DNA. Still having access to the world’s knowledge, but interfacing with humans in a whole different way. One that solves not for speed, but for the learning and growth of the recipient. Solving not for volume of information, but for how much a person truly “gets” an idea, and is motivated to act on it. This is an AI that truly understands how humans learn and grow, that can read the mental state of people in real time and know just how to support them in that moment.  How should this kind of AI be measured? Not by the speed with which it provides an answer. But by its success rate at conversations that make people better managers and leaders.   Fortunately, we’ve been working on this idea for 26 years. Ready to learn more? Reach out and book a demo of our AI named NILES, and see it in action for yourself.  –> Book a Demo Here

By Emma Sarro, PhD and Laura Cassiday, PhD Maria, a mid-level manager at a tech firm, sits at her desk staring blankly at yet another meeting invite. Lately, her days feel like a blur of back-to-back Zoom calls, shifting priorities, and constant fire drills — with little recognition or clarity from senior leadership. Once energized by leading her team, she now finds herself just going through the motions. The sense of purpose that used to drive her has slowly faded, replaced by a growing sense of detachment and fatigue.  Maria’s experience is becoming the norm. According to the Gallup State of the Global Workplace 2025 report, managers are not okay. While overall employee engagement dropped from 23% in 2023 to 21% in 2024, and individual contributor engagement, while low, at 18%, remained steady over the two years, manager engagement saw a steeper decline, falling from 30% in 2023 to 27% in 2024. The trend is especially alarming for young and female managers, who were the most affected, dropping by 5 and 7 percentage points, respectively. All of this occurred over the period of just one year. Manager disengagement should be viewed as an early warning sign for team disengagement. It’s difficult for an individual contributor to care deeply about their work when their manager is just going through the motions — and employee disengagement affects team performance, productivity, and employee retention. Gallup estimates the recent 2% dip in global engagement cost the world economy a staggering $438 billion. To reverse this trend, organizations must focus on re-engaging their managers, which in turn could help drive engagement among the rest of the workforce.  Increase manager training Lack of role preparation may be a key reason for the burnout and disengagement managers are experiencing. In fact, the Gallup report reveals that only 44% of managers worldwide have received management training. Even those who have received training are encountering entirely new situations. At NLI, we’ve found that roughly half of the skills leaders need today are new, such as building AI fluency within their team, while the other half are just harder to practice, such as helping their team make swifter, unbiased decisions.  NLI’s LEAD program was designed to help leaders develop the skills needed to navigate today’s complexities. LEAD provides the essential skills for all leaders, at all levels, using a brain-based framework that helps learners build skills to manage themselves to optimize their own performance, mobilize others to push their team towards high performance, and drive results to make better decisions under pressure and remain agile through change.   Democratize coaching with AI tools The value of coaching lies in the tailored insights it leads managers to—insights that turn into meaningful action. For leaders like Maria, a coach could help her identify the root of her disengagement and reconnect with her purpose. However, coaching can become very expensive when scaled across all managers in an organization. It could cost over $1.2 million per year for 100 managers.  But with dedicated leadership AI tools, every manager could receive coaching in the flow of work, effectively democratizing coaching. For example, an AI coach like NLI’s NILES costs only $30/month per manager, or $36,000 per year for 100 managers. NILES integrates into a manager’s workflow, providing real-time coaching, mentoring, feedback, and role play, all informed by a layer of research-backed “neuro-intelligence” — a specialized neuroscience-based programming that works with your brain’s natural patterns for insight, decision-making, and social interaction. For example, if Maria felt overwhelmed by shifting priorities, NILES could help her structure a team meeting to sync expectations, a foundational habit of proactive accountability, ensuring everyone is aligned and clear.  Establish a feedback culture In many organizations, feedback is a top-down, once-a-year event during a performance review. For managers like Maria, the silence from senior leadership is demoralizing, leaving her to wonder if her work has an impact. This lack of connection is likely a major driver of managers’ disengagement. To remain engaged and aligned with organizational goals, managers need both positive and constructive feedback. Building a true feedback culture requires a top-down shift that reimagines how feedback is given — enabling it to spread throughout the whole organization. When senior leaders regularly model asking the managers under them for feedback, it immediately reduces the inherent status threats of feedback, creating a rewarding and constructive interaction instead. When managers ask for feedback from their direct reports, they signal that feedback isn’t so scary and should actually be sought out. Over time, the manager’s team will become feedback-seeking, too, asking their manager for feedback to get better themselves.   When Maria’s boss asks, “What’s one thing I could be doing to better support you?” it not only makes Maria feel valued but also gives her a model to replicate. This simple act opens up dialogue, builds trust, and helps her feel more connected and effective, co-creating success with her team. Managers are like a canary in the coal mine for the entire company: When they’re disengaged, others soon follow. But it doesn’t have to be this way. By supporting their managers through increased science-backed training, scalable AI coaching, and a robust feedback culture, organizations can reverse this trend. With new leadership insights and tools, busy managers like Maria will rediscover their purpose, more effectively lead their teams, and leave positive impacts on the organization.