8 hours ago
AI Expands Our Capacity, But Are We Expanding Our Skills?
Asian woman watching hologram screens. Business and technology concept. Smart office. GUI (Graphical ... More User Interface).
Nearly 25 years ago, our HR business partner team was facing a challenge similar to what we are experiencing today with AI adoption. As we transitioned to a shared services model, we recalibrated not just how work got done, but also what work was most valuable. The 'less valued' transactional tasks that most HR business partners wanted to offload, like answering questions about benefits, running headcount reports, and managing performance issues, were the very things that gave them their sense of worth. What appeared to be resistance to a changing strategy was actually resistance to a changing identity.
As an HR business partner, I had been preparing for a more strategic role through graduate studies, doing some external coaching work, and practicing what I was learning with the leaders I supported. I knew the skills needed to be a 'strategic HR business partner', and while I didn't have all of them, I was clear on the gap I needed to close. However, many of my colleagues had not confronted that deeper question of what 'strategic' really meant and the skills they needed to acquire and practice to become that.
Today, as AI promises to automate routine work, we're seeing the same pattern. On the surface, employees are resisting the use of technology and AI tools, but what they are ultimately resisting is the change to their identity. The roles they have played, the workflows they have been part of, even how they are expected to communicate is changinging, yet most leaders are not being clear about what those roles and that identity is evolving to. Is the new identity that we are supposedly carving out for them better than the one they have? Would it be better for them to resist and continue to have a healthy level of skepticism until they better understand what is expected in their new work context?
Beyond identity, I am also seeing the skills gap that is not being addressed. How are organizations supporting employees in not only learning AI tools, but in helping them develop new skills that they need to learn with all that extra time? The cultural shift we underwent in HR so many years ago was a two-way contract. It was we, as HR Business Partners, agreeing to change, but also our managers and HR leadership clearly articulating what that change looks like and how they were going to help us get there. The option was clear: either we evolve to become more strategic, partnering with business leaders differently, move into a more operational role, or leave the company altogether. Some HR business partners chose to move into the shared services center when they realized they genuinely enjoyed the transactional work they had spent years trying to escape. Others left the company to continue doing the very work they tried to escape from for so many years. Most of us who stayed shared one major mindset shift. Rather than asking, 'Which tasks are being taken away?' we asked, 'Which behaviors and skills do I need to develop to deliver greater value to the business?' And we made sure we had a development system that was set up to learn and practice those skills with each other and our leaders.
AI is taking over more of the transactional work, but are we ready to tackle the strategic work it now makes possible? Before rolling out another AI tool, organizations must demonstrate to employees how this shift benefits them as well as the business and provide them with the skills to work effectively alongside AI. The real question is no longer,
'What more can we get out of our employees with AI?', but rather,
'What more can we do for and with our employees and AI?'
A recent Stanford study showed that while 83% of employees in China see AI as an opportunity for growth, only 39% of U.S. workers share that optimism. We are throwing tools, stats, and training at people in the name of more productivity and efficiency without connecting those things to what matters in an employee's day-to-day workflow—no wonder we are not excited in the US.
The fundamentals of Change leadership include explaining why we are changing, what is changing, and how we are helping people change. Yet, every day, we continue to launch another internal AI sandbox and announce that usage will be tracked and measured. When has counting course completions ever guaranteed that employees are adopting the change and gaining the skills they need?
Most organizations today see the opportunity of AI through two lenses:
The productivity lens: 'Do more tasks per hour' and the efficiency lens: "Process every request faster."
But what if we could be more productive and efficient while also giving employees additional opportunities to grow and develop those skills they will need to be more strategic when they are being more productive and effective with their time?
What if instead of asking, 'How can we do more tasks per hour?" we ask:
'How can I use the time I get back from leveraging AI on more strategic work?"
When people see that their company is leveraging AI as an amplifier to their work, rather than outplacing them, they will more readily dive into identifying opportunities where AI can free them up to focus on higher-impact activities.
Here are two examples from Moderna and Klarna in how they have approached the 'why, what, and how' of leveraging AI with human augmentation.
Moderna's shift to "work planning" from 'workforce planning' in the context of AI is a great example of this.
Moderna's 'Why': create a more integrated strategic road map that not only increases opportunities for drug discovery but also allows employees to rethink workflows.
Moderna's 'What': Develop over 3,000 tailored versions of ChatGPT, called GPTs, designed to facilitate specific tasks, like dose selection for clinical trials and internally, address basic HR questions related to performance, equity and benefits.
Moderna's 'How': Redesign and reimagine how technology and people interface by merging HR and IT under one Chief People Officer. Moderna is also upskilling employees, helping them to leverage that productive time that they got back on more strategic work.
What if instead of asking, 'How can we do more with less?' we ask:
'How do we ensure we are focused on the right priorities?'
We know that being efficient alone isn't going to get us the results we want. Without deliberate human judgment, AI will only amplify hustle habits that keep us busy with everything, rather than prioritizing the few things that truly matter.
Klarna's experience illustrates the risks of prioritizing efficiency solely over effectiveness. Their journey illustrates why focusing solely on speed and cost reduction, rather than both employee and customer value, ultimately leads to less effective results and a significant disconnection with employees.
Klarna's 'Why': Klarna's CEO gave a clear 'why' to employees on using AI, but it didn't include developing or upskilling employees. It was solely focused on leveraging AI as much as possible to address customer service questions, disregrding the long-term impact and potential scenarios of letting go of 700 representatives.
Klarna's 'What': After replacing customer service representatives with AI, they had to reverse course when they realized they'd "amputated" empathy from their customer interactions.
Klarna's 'How': Today, they've adopted a hybrid approach where AI handles simple queries while humans manage the more complex cases.
When AI handles the transactional load and we empower people to think strategically, we do more than speed up work; we redefine it. Instead of setting AI and humans in opposition, let's reinforce what they can accomplish together: higher productivity and efficiency, but also greater strategic leverage.
In your next 1:1, open up a discussion about AI beyond how much they are using the tools. Ask them how they are leveraging their time now that AI is doing more of the tactical tasks. Ask them what support they need to keep doing that kind of strategic work. Clarify the skills you would like to see them build and ask how you can support them in developing those skills. It's through these kinds of discussions that we can continue to work strategically with AI, not against it, with humans leading the way.
