The year is 2030. As a talent executive, you manage a suite of talent processes, overseeing the work of several hundred managers — how they hire, set goals, and evaluate performance. But you don’t go through these phases of work alone.
Beside you is an AI partner that assists both you, and all your managers, with every stage of the employee talent life cycle. It helps you screen and interview candidates more effectively and with less bias; set employees’ goals and stage check-in meetings that are maximally productive; and support you and your managers to have rich and inspiring feedback discussions at the end of each quarter to drive greater performance. This AI is giving managers real time coaching on how they support their employees, and then helpful insights to you as the head of talent about the managers doing well, and those who might need a little extra support.
Seems like a dream? Or to some, maybe a nightmare?
To make this possible would require decades of research. You would have to train an AI to understand the whole world of work, including goal setting at different levels of management; understanding the cognitive challenges of busy, bias-prone, emotional humans; and it would need to know how to interact with a highly driven user who doesn’t like being told what to do, helping them grow in a nuanced and relevant way. And all of this would need to be wrapped into the same AI that can work fluently with managers.
As it turns out, these are the capabilities we’ve been building over the past three decades.
Meet NILES, the Neuro Intelligent Leadership Enhancing System, an AI partner who’s designed not to replace human managers (even if some people may end up preferring an AI leader someday) but to support human thinking. With NILES, talent teams can supercharge their intelligence and accelerate their effectiveness, both individually and across the entire workforce.
The Present Is Stuck In the Past
Performance management today runs on an antiquated set of technologies, which are slow and full of bias. As a result, the quality of talent development remains stagnant or, worse, actually regresses. While the world gets more complex and moves more quickly, employees are left with hand-me-down systems and processes, which their leaders don’t believe in or use effectively. These gaps exist across every stage of the talent cycle, from recruiting and hiring all the way to promotion and exiting.
The model itself is flawed, too. Current talent systems rely on small teams doing large volumes of time-heavy assessments, such as 360 reviews, while being expected to give thoughtful, personalized feedback. In an organization of 10,000 employees with 1,000 leaders, such a talent team might be made up of just 10 people who are equipped to spend time with only 100 or so managers, and really close time with just five or 10. The math doesn’t make sense, and it can’t produce the right results. Determining top talent becomes more of an exercise in clever guessing than true fact-finding.
AI holds the promise to make this obsolete system more efficient and effective. In a matter of seconds, NILES can produce far more insights on a macro scale than individual humans who are already stretched thin. Which, when multiplied across an entire organization and over time, can yield far more accurate, personalized assessments of job candidates, top performers, employees who are struggling, and areas of development across the entire workforce.
In other words, instead of 10 people trying to serve 1,000 managers and 10,000 employees on their own, NILES can help that team of 10 support the whole company by shouldering key tasks and developing all 1,000 managers every month or week, a level of impact no human team can match.
Against this backdrop of innovation, we see three key domains where NILES can improve talent processes to accelerate organizational success: hiring, collaboration, and performance management. Let’s look at each a bit more closely, but first, a word on separating an effective AI from the rest.
NILES the Talent Accelerator
What makes NILES the ideal partner to accelerate an organization’s talent processes is a critical layer of “neurointelligence.” That is, NILES doesn’t just spit out answers to users’ queries. It’s equipped with a level of metacognition that perceives patterns in users’ speech to detect hidden biases or strains of thought. For example, have NILES listen in on your next presentation and ask it afterward for feedback on your speaking style and the quality of the ideas. It will give you detailed notes on how you did, based on signals it picked up during the meeting.
The impact? It makes people smarter, faster. Research shows typical AI chatbots don’t tend to make us much smarter because they supply answers, stemming curiosity or further creative thinking. NILES, however, is designed to prompt further reflection, getting people to arrive at “Aha” moments on their own, which other research shows are among the most potent motivators we experience, because they come from within.
Neurointelligence doesn’t just apply to coaching. It also has massive implications as the operating system powering a set of talent functions. Now we can see how NILES accelerates the three domains we just mentioned: hiring, collaboration, and performance management.
Hiring
Sam is hiring a new sales director to lead his team of seven salespeople. He knows he has a history of hiring people like him — warm, extroverted, competitive — but questions if the next hire should follow this pattern. Sam has a discussion with NILES to check these latent biases, where he asks NILES about ways to make his interviewing fairer and more inclusive through smarter questions and better indicators of the candidate’s qualifications.
It turns out, NILES suggests Sam’s team will function best if he shakes things up this time, given research showing diverse and inclusive teams outperform more homogenous ones. NILES also supplies Sam with sample personas of ideal candidates and interview questions designed to elevate key skills and traits, especially those Sam might have missed on his own.
When Sam eventually goes into the recruiting and interviewing phases, he does so armed with brain-based strategies for finding the ideal candidates. With the candidate’s permission, NILES can also be listening during the interview, debriefing with Sam afterward on how well he stuck to the approach the two of them hashed out earlier. Here, NILES becomes both a talent coach and an accountability partner, to further Sam’s leadership development overall.
Collaboration
Ken and Marta are colleagues on a small marketing team. They meet weekly to review ongoing campaigns and brainstorm new ideas. Lately, they’ve felt stuck. None of their new ideas feel particularly innovative or clever. So they decide to recruit help from NILES.
In their next meeting, Marta has NILES listen in on the first half of their sync, where they review the latest numbers. Then, before proceeding to the second half where they typically brainstorm, Marta stops to ask NILES for help in framing up the creative portion of the meeting. What did it notice about the way Ken and Marta discussed the key metrics? What about their individual conversation styles or apparent mindsets toward the work did it pick up on?
NILES shares that Ken seemed to have a fixed mindset about the current strategies. He used language like “good” and “bad,” rather than seeing possibilities in the data. Meanwhile, Marta, according to NILES, seemed to shut down when Ken slipped into this mode, suggesting she may have perceived a threat to her status. NILES recommends a new approach: one where Ken focuses on keeping an open mind and Marta recognizes she may be sensitive to status as a social driver.
Moving forward, both team members can collaborate with greater awareness and form more productive habits for working together.
Performance management
Judith works on the senior talent team, reporting to the Chief People Officer. Her job involves systematizing how hundreds of employees are evaluated. It’s a lot of work, and she feels ill-equipped to judge roles where she doesn’t claim any expertise. Luckily, her organization chose to integrate NILES into its entire performance management suite.
One of the key ways Judith uses NILES is during goal-setting season. At the highest level, her team works with NILES to sketch out the organization’s goals for the entire year. From there, each quarter Judith creates prompts that she sends out to managers across the organization. Her request is for each manager to feed the prompt into NILES so that the manager and NILES can discuss goals for that quarter. Then, the manager will send the synthesized version of that conversation back to Judith so she can reconcile them alongside the company’s goals.
She also takes things a step further. Each month, as managers check in with NILES about their progress toward the goals, Judith sends a separate prompt to facilitate the discussion, the outputs of which then get sent back to Judith for similar review.
The total output from this system is far greater than Judith could have accomplished in months or years working on her own. As a result, she’s able to “be everywhere” through the distributed power of NILES, which helps her drive better outcomes rooted in data, rather than rely on legacy systems built on flawed assumptions.
These three examples are just a small sample of the many use cases where NILES can help talent teams, frontline managers, and employees work more effectively and achieve better outcomes. That’s because wherever there is a human process, there is a high likelihood the process contains some element of bias and human error. NILES’s value lies in minimizing those instances, accelerating performance across the entire organization, and helping every team member become the best version of themselves faster than they ever thought possible.
Click here for more information and a free trial of NILES.
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