Accelerating L&D With AI: How to Lead, Adapt, and Keep the Human Touch

BY Katie Chambers | December 17, 2025

Nearly 60% of HR leaders say AI adoption is one of their biggest challenges, yet the prospect of radically improving worker learning and development is a huge new opportunity. 

How can AI make L&D more individualized, efficient to produce, and integrated with the flow of work? Can it upskill workers more quickly than traditional methods and accelerate leadership development? Leaders shared their ideas on the subject during a panel discussion titled, “Accelerating L&D With AI: How to Lead, Adapt, and Keep the Human Touch,” at From Day One’s Miami conference. 

“The best companies in the world that are going to develop through this phase are the ones that train their people to use AI most effectively, not be scared of it, and embrace it,” said Dave Coldwell, global AI executive at Cisco. But that’s easier said than done. “With AI, like any new technology, there is some apprehension, and we all know that it’s a tool. It’s not human,” said moderator Paul Bomberger, independent journalist and former Miami Herald business editor. 

Leaders must maintain human connections with their teams while rolling out emerging technologies, and emphasize that these tools will never replace human workers—just augment them. “It doesn’t have innovation. It is good at giving you resources and instructions, but there’s the human aspect that we need too,” said Elyse Sitomer, learning & organizational development partner at Memorial Healthcare System.

It can be hard to get “old school” industry leaders to get on board with the AI revolution. Alexandra Bautista, SVP of employee experience at Harvard Services Group, said the key is “helping them understand that it’s a tool to leverage your performance.” She has brought in speakers to share how AI can make the workday easier and reinforce that it’s a positive rather than something to be feared. 

Panelists suggest rolling out simple tools like Microsoft Copilot or ChatGPT to get your general workforce more comfortable with artificial intelligence. These tools can simplify administrative tasks by summarizing email chains, creating agendas, or taking notes at meetings. 

From there, more complex AI educational software packages are no longer one-size-fits-all, but highly individualized, says Chris Narmi, chief strategist, AI and workflow at HP. These tools “recognize the strengths and weaknesses of an individual, track them through their learning process and customize their learning program.” And the training is often built in. “AI is unique in that it’s the first technology that can really teach you how to use it.”

Innovative Uses for AI in the Workplace 

Gone are days of lengthy employee handbooks or boring onboarding videos. “What generative AI has allowed us to do at Cisco is personalize the training. [We have] the right training for the right people at the right time, and that’s led to developments in leadership, developments in creativity, and exponentially improv[ed] our salespeople’s engagement with the customers and partners that they’re dealing with on a day-to-day basis,” Coldwell said. 

“The thing that’s uniquely human is intuition, empathy, and purpose, which we don’t have just by using AI alone.” His organization has developed its own AI model, called Circuit, used by its 20,000 salespeople. “Instead of replacing people, it’s actually helping to skill up our new employees, but also for our existing employees, it’s helping empower them to be better.” 

Maria-Pia Barbona, VP of HR at Swatch Group, shares that in her previous role at LVMH, her team worked with tools like Yoodli, an AI speaking coach that let salespeople roleplay customer interactions. “You prompt your AI, you go into a FaceTime call with your AI, and there’s a person that you see there and you go in a roleplay,” she said. The platform lets associates practice difficult conversations and refine their techniques to make a sale. Managers were able to log in to see results, which helped them discover trends as to which areas required further training. 

Panelists spoke about "Accelerating L&D With AI: How to Lead, Adapt, and Keep the Human Touch" 

Narmi cautions that AI can provide solutions to customer issues, “but it lacks the empathy to understand the applicability of those answers, and you’ll learn that you need to apply your own judgment. The human piece is applying that [artificial] intelligence appropriately under a set of circumstances.” He advises engaging in active dialogue with AI to hone its answers, guiding it with your own human emotion and intuition. “I find it a collaborative process: it learns from me and gets better.”

AI works best when it’s breaking down large swaths of information, providing summaries, and giving detailed explanations. Then you need to synthesize all of it in the complex, innovative, and nuanced ways that AI can’t. “I like AI for its immediacy. It gets the hard work out of the way,” Sitomer said. 

Narmi shares that he has developed a fleet of AI agents through Copilot to help him optimize his performance. “I have an executive assistant. I have an editor. I have a white paper writer.” 

At Harvard Services Group, Bautista and her team create GPTs that offer a customized learning path for new hires during the first 30, 60, and 90 days of their employment, creating a “learning culture” at the organization that did not previously exist. “We’re taking it to the next level, starting next year, and customizing based on performance conversations with the managers. Where are those skills gaps that this person may have? Do we want to get them to the next level? If so, what are the competencies that they need to have?” she said. Employee retention is the goal. “I think there’s no other way to tell our employees that we care than to tell them we see you. We want to develop you. We want you to grow.”

Narmi advises that leaders remember that AI is just a tool; an organization’s biggest asset is still its human workforce. “Recognize that your talent, and the fundamental talent of the people that work for you, is imagination. You need to foster imagination and help people to understand that AI cannot perform that role,” he said. “Let it do the research but let people use their imagination with the AI to expand [their] ideas.” 

Or, as Coldwell put it, “AI is for speed. People are for direction.” 

Katie Chambers is a freelance writer and award-winning communications executive with a lifelong commitment to supporting artists and advocating for inclusion. Her work has been seen in HuffPost, Top Think, and several printed essay collections, and she has appeared on Cheddar News, iWomanTV, On New Jersey, and CBS New York.

(Photos by Josh Larson for From Day One)

Related Stories

AI in HR: How Work, Skills, and Leadership Evolve in a New Tech Era

A year ago, HR leaders approached artificial intelligence with trepidation, afraid to jump in first, lest they also be the first to make a mistake. “That really changed overnight,” said Adam Vassar, head of talent science and learning design at skills evaluation platform CodeSignal. Early adopters follow a familiar pattern: automating the top of the recruiting funnel or using AI to assess technical skills like coding. Today, the use cases are broader and more varied. Vassar now works with clients to evaluate employees–technical and non-technical alike–on generative AI literacy, role-specific AI proficiency, and understanding of the technology’s limitations.Vassar and his fellow panelists discussed how AI is reshaping jobs, and how HR is helping to manage that shift, during a From Day One webinar on how work, skills, and leadership are evolving in the age of AI.“But before we can evaluate candidates on the AI skills they need or target the skills employees need to develop, we have to redefine skills taxonomies and job architecture,” Vassar said.That’s the work currently underway at data engineering firm Innodata, says Charlie Tañala, head of talent capability and development. “The foundation is clarity,” Tañala said. “You need a skills taxonomy that reflects the work your organization actually does.” The project, launched less than a year ago, will undergird Innodata’s internal skills marketplace, enabling the company respond more quickly to client needs and employees to move fluidly within the organization.Journalist Emily McCrary-Ruiz-Esparza moderated the session (photo by From Day One)Innodata accelerated its focus on AI skills as it gained a wave of AI-proficient clients, and their existing client base was quickly catching up. “We started supporting customers who build and refine generative AI models, and the expectations moved to a different level,” Tañala said. “The skills required in generative AI workflows are more specialized and more judgment-heavy. We had to rethink almost everything–how we attract talent, how we design roles, and how we structure teams.”What AI skills a workforce needs will vary by company and function, says Marvie Wright, the VP of HR at customer service provider Qualfon. “Spend time in discovery to understand what’s out there,” she said. “Then tailor that to your organizational needs, being aware of what gaps you have, and how would you like for an AI to fulfill those.”AI is being applied differently in finance than in, say, communications or IT, prompting employers to think more deliberately about how skills are developed across functions. At Qualfon, a cross-functional task force evaluates and sets expectations for AI skills by department. “We know this is leading to a more enhanced future,” Wright said. “It’s really exciting, and it’s going to change the educational forefront of the workplace as well.”Identifying and measuring skills is only part of the equation. Training is another. “You want hands-on experience to see what’s possible, explore the edges, and understand where the logic breaks down,” said Ari Lehavi, head of applied AI at credit ratings institution Moody’s. He favors group workshops that demonstrate what’s so satisfying about AI, which is the ability to go from zero to prototype in hours.Participants collaborate–bolstered by AI–to solve real problems, moving from concept to execution. “I like to see how different people come up with ideas,” Lehavi said. “You help when they struggle, and, typically, you end up with some great ideas,” he said. “Everybody builds something, and they get very proud. That whole element of fear and the unknown dissipates, and they can venture into new ways of operating.”Wright advocates for as personalized an approach as possible. “We look at their individual needs, their gaps, and their progressions, then tailor individual approaches for each one very quickly and very accurately,” she said. As Qualfon has intensified its efforts, the returns have come faster. “We love it. We’re obsessed with it right now.”For Tañala, it all comes back to adaptability. “The skills we rely on today can change quickly,” he said. “Our people need the confidence to adjust without feeling lost. AI readiness is about understanding how to work with AI—and how to make good decisions with what it produces.”Editor’s note: From Day One thanks our partner, CodeSignal, for sponsoring this webinar. Emily McCrary-Ruiz-Esparza is an independent journalist and From Day One contributing editor who writes about business and the world of work. Her work has appeared in the Economist, the BBC, The Washington Post, Inc., and Business Insider, among others. She is the recipient of a Virginia Press Association award for business and financial journalism. She is the host of How to Be Anything, the podcast about people with unusual jobs.(Photo by Harsa Maduranga/iStock)

Emily McCrary-Ruiz-Esparza December 17, 2025

How AI Can Work as a Partner to Augment Human Capabilities, Rather than Replace Workers

Imagine having a new team member who shadows your best salesperson to fetch data and learn unspoken rules, like why one client is more responsive to a direct approach while pitches have to be carefully framed for another. This apprentice never forgets a lesson and shares their nuanced understanding with colleagues. That’s the vision of AI that Ari Lehavi, the head of applied AI at Moody’s, is bringing to life, shifting the focus from task automation to capturing and scaling the institutional wisdom that companies are built on. Lehavi shared this idea and more during a fireside chat at From Day One’s December virtual conferenceThe transformative potential of AI lies in human-AI collaboration based on a continuous, two-way learning street that’s designed to augment human judgment rather than replace it, he told moderator Rebecca Knight, contributing writer at Harvard Business Review. Shifting From Automation to AugmentationAI-doomers often frame the technology as the worst thing that’s happened to job security in human history, but Lehavi sees it more as a collaborative tool that enhances human performance and encourages organizations to do the same. Ari Lehavi, general manager, head of applied AI at Moody’s, spoke during the fireside chat (company photo)“I do think that there’s been some orientation around thinking about AI as a way to generate efficiencies and automation, and I don’t think that’s the best use of AI,” he said. “Increasingly, I’m seeing a shift in the way that companies are thinking about it as an accelerant of performance, rather than as a way to generate efficiencies.”The central question then becomes how to increase productivity and work quality with AI. Lehavi says one of the ways that organizations can accomplish this is by using AI to handle simple, repetitive tasks, freeing up employees to focus on work that requires uniquely human skills, such as judgment, empathy, and innovation. “The hard cases, the edge cases, the complex areas, the mentoring of other people, the management, the development of skills in other individuals, the expansion of what’s possible in their role,” Lehavi added, pointing out what humans excel at. The Importance of Bi-directional DesignLehavi says “bi-directional design” is necessary to optimize human-AI collaboration. Most AI tools used today have a single directional design. You ask questions, and it answers. True partnership requires a feedback loop where humans teach AI context and nuance, he says. “AI has information that it can pick up from documents, from data that can help you assemble research faster,” Lehavi said. “But that has a very limited kind of lift that it creates.” The exponential gain happens when AI begins to understand how and why you make decisions. “It has to kind of almost get into your head.”AI provides value, like summarizing key points from a large text library, in a bi-directionally designed system, but it also identifies gaps in its understanding. It learns to ask questions such as “Why did you make that decision?” This leads to humans working with AI, explaining the nuanced instincts that come with experience. Capturing the reasoning behind human decision-making enriches the AI model's understanding, allowing it to provide more insightful recommendations in the future. The information learned by the AI can be packaged and shared, creating a “collective organizational wisdom” that other employees can access. A Concrete Case: Augmenting the Sales ProfessionalLehavi shared an example of how bi-directional communication between humans and AI works in the real world from within Moody’s sales department. A standard CRM stores data, but misses the subtleties that define a veteran sales rep’s success. Insights like the unspoken politics of a client company, the specific pain points a key decision-maker is sensitive to, or the historical context of a relationship. Moody’s built a system that starts by giving sales team members AI-generated leads, matching market pain points to the solutions it provides. The AI responds with questions such as. “Tell us what we don’t know, tell us, you know this person,” Lehavi said. “We know the general profile, but we don’t know this particular relationship in this particular instance, and what exactly is the dynamic that would make this deal move faster and closer.”The seller feeds the nuance context back to the AI, which then refines its recommended messaging and value propositions. The system also identifies patterns in these seller-client relationships and provides recommendations such as: “What you’ve told us about this individual and this company seems a lot like three others that we’ve encountered, and this framing of this message really resonated.” The sales team member tests the hypothesis, and the result, positive or negative, is fed back into the AI model, expanding its institutional knowledge. Lehavi views AI more as an apprentice than an intern. “Initially, the apprentice gets more value from you than you get from the apprentice,” he said. You invest time teaching the algorithm your ways, then the dynamic eventually flips. “You’re starting to get that much more value. And then you know that you have a true partner, so you can move up to the next level in your career.”With AI managing more of the administrative burden and research, sellers have more time and mental space to focus on the irreplaceably human aspects of their role: deepening relationships with clients and crafting persuasive value propositions. For leaders, it means scaling the impact of top performers, so other employees benefit from the institutional knowledge they help build. The Undocumented Layer of Human JudgmentThe critical insight Lehavi stressed throughout the conversation is appreciating the vast, often invisible complexity of most professional roles. He points to what he calls “the undocumented layer of human judgment” that exists in every position, from customer service to legal departments. Studies suggest that around 10% to 40% of what knowledge workers do is based on this tacit understanding.“Whenever I see enterprise implementations that end up where people kind of feel like they didn’t accomplish what they were supposed to accomplish, I often link that to the underappreciation of how much of the work that gets done is unwritten, and is based on judgment and experience,” Lehavi said.The routine portions of a job that knowledge workers spend 60% of their time on might be automatable. But the high-value edge duties, where crucial relationships depend on nuanced judgment, are where human-AI collaboration must focus. The goal is to design systems that bring the right information and context to the surface to help their human counterparts make faster, more-informed decisions. Lehavi advises companies to build systems that ask “why.” AI models that learn from human experience and improve the performance of their human collaborators. This allows organizations to move beyond simply automating tasks with AI, and start codifying, scaling, and institutionalizing their collective knowledge–their most valuable asset. Ade Akin covers artificial intelligence, workplace wellness, HR trends, and digital health solutions.(Photo by KTStock/iStock)

Ade Akin December 16, 2025

How to Introduce and Leverage AI at Work Without Stirring Up Resistance

The rise of generative AI at work brings excitement, uncertainty, and a touch of paranoia, from fears of job security, to leadership’s ethical concerns, and worries of its power. David Wishon, SVP of talent management at Lionbridge, says the key to successfully rolling out AI at work is surprisingly simple. “We started with carbonara recipes, and what dogs should you have in a New York apartment,” Wishon said during a panel on AI adoption at From Day One’s Boston conference. “We started with fun, and then that created this momentum.”This playful approach was central to Lionbridge’s strategy for demystifying AI. The company addressed employee fears about AI by giving each employee a goal to accomplish with generative AI for the year, says Wishon. Lionbridge trained 4,500 of its 6,500 employees in a few months by starting with low-stakes, personal use cases for AI, before transitioning to work-related tasks. “It was really just trying to get that sense of fun, that sense of permission,” he said. Demystification and the Soft LaunchWhile Lionbridge opted to introduce AI with structured, company-wide training, other organizations embraced a subtler approach. “Ours was almost more like a soft launch,” Michelle Randall-Berry, the global head of talent at Teradyne, said. “We didn’t go through a lot of discussion and approvals. We just did it.”Teradyne’s talent acquisition teams and learning department quietly integrated AI with gentle “nudges,” such as personalized course recommendations for employees and automated messages to potential hires. “It was kind of more of a quiet, ‘wow, believe it or not, we’re using AI, everyone,’” Randall-Berry said about Teradyne’s subtle approach to AI integration.Streamlining Workflows and Enhancing PerformanceAnkit Saxena, the global head of people insights and HR technology at PPG, says AI’s most significant impact in most organizations is increased efficiency. PPG, an international manufacturing company, created its own version of ChatGPT called “Chat PPG” for internal use, providing employees with unbiased, vetted information. Panelists spoke with Janelle Nanos, assistant business editor for news innovation, the Boston Globe about "How HR Leaders Can Leverage AI to Make Their Work More Effective and Fulfilling"PPG accelerated its hiring cycle by delegating processes like interview scheduling and candidate screening to artificial intelligence. “Instead of X number of days, it is reduced to X minus 10,” Saxena said.The benefits of embracing artificial intelligence extend to performance management, a traditionally time-consuming process for managers. “Performance reviews can take several hours,” Marissa Gladstone, the director of sales at Workleap, said. AI tools can aggregate an employee’s work, projects, goals, and feedback, into a holistic summary in minutes. This changes the manager’s role from data collector to coach, allowing them to focus on “true relationship building.”The Human Guardrails: Bias, Fraud, and BurnoutAI integration into organizational processes also brings some inherent risks, particularly around biased algorithms and candidate fraud. All five panelists unanimously agreed that artificial intelligence is most efficient when it assists the hiring process, but doesn’t make final decisions. “We determined that we weren't going to use AI for assessment and decisioning of candidate quality,” Wishon stated, pointing to ongoing legal cases such as the Equal Employment Opportunity Commission (EEOC) vs. iTutor Group in 2022. iTutor agreed to pay a $365,000 settlement after its AI system was found automatically rejecting applications from women over 55 and men over 60. Saxena outlined a three-part governance framework used to prevent AI from inheriting bias at PPG: verifying data sources, scrutinizing vendor algorithms, and continuously evaluating outcomes for discriminatory patterns.AI is creating a new frontier of fraud that hiring managers must look out for. Wishon described “impostors or dreamers” who use large language models to fabricate resumes and answer interview questions in real time. Wishon also points out the rise of “collusion,” where data centers use artificial intelligence to imitate individual candidates. In response, Lionbridge now uses identity and email verification checks to filter for “viable, authentic, accurate candidates.”Wishon says the most unexpected challenge he’s faced working with artificial intelligence is what he terms “AI burnout.” He says the initial efficiency gains AI brings have a lifespan and cannot accelerate human-centric elements like socialization, change management, or navigating company culture. AI as Your Sparring Partner, Not Your ReplacementDespite the challenges of integrating artificial intelligence into company processes, AI works best as a collaborative tool rather than a replacement for human intelligence, creativity, and intuition, the panelists agreed. AI’s role is to empower, not replace, the human workforce. Gladstone, who admits to her own moments of fear, now sees AI as an essential partner. “AI is not going to replace you. People who use AI will,” Gladstone said. “AI is your first draft. AI is your sparring partner. It is something that helps you develop some of those ideas. It takes away that analysis paralysis.”“Just dip your toe in,” said Randall-Berry, who recently coached a nervous team member on using Copilot to refine a memo. That same team member couldn’t get enough of AI once she got past her initial hesitation. “She was absolutely floored,” Randall-Berry said. “And then she kept asking it, ‘Can you do this? Can you add this?”Ironically, the ultimate destination of AI integration is a profoundly more human workforce, where employees focus on tasks that require a human touch, while AI handles repetitive, manual tasks. Less administration, more human connection. Fewer processes, more creativity. Ade Akin covers workplace wellness, HR trends, and digital health solutions.(Photos by Josh Larson for From Day One)

Ade Akin November 24, 2025