As AI continues to rewrite the rules of work, leaders are having to rethink how their organizations operate while keeping up with technology that seems to advance by the day. The impact reaches across the business, from how work gets done to where companies invest and how they plan for the future.
At the same time, leaders have to prepare their people for whatever comes next. How will roles change? What skills will people need? Where will human judgment matter most as technology becomes a bigger part of the work?
You don’t need to predict exactly where AI is headed to start preparing your workforce. Here are four areas to focus on now:
1. Redesign the Work Before You Reskill the Worker
It can be tempting to start workforce planning by asking what AI skills employees need. But it may be more useful to start one step earlier: How should the work itself change?
Future-of-work expert Kelly Monahan compares AI to the invention of the elevator. Elevators didn’t just make it faster to move between floors. They made skyscrapers practical and helped reshape how buildings and cities were designed. AI offers a similar opportunity to reconsider the blueprint of work, rather than simply make existing processes faster.
Start by breaking roles down into the work people actually do:
- What can AI do well?
- What should people continue to own?
- Where do judgment, trust, relationships, or personal voice matter?
- Is AI simplifying the work or adding new layers of oversight?
That last question is worth asking. Generative AI can introduce more variability into a process, which may create additional work for the people reviewing it.
Once you have a better picture of how the work could change, it becomes easier to see how roles may evolve and what skills people will need next.
Prepare People to Exercise Judgment, Not Just Use AI
Knowing how to use AI is one part of AI literacy. Employees also need to know when to question it and when human judgment needs to take over.
Vinh Nguyen, former NSA Chief Responsible AI Officer and Senior Technical Advisor at a leading frontier AI lab, describes AI as probabilistic rather than deterministic. It produces probabilities, not guarantees, which means a useful answer isn’t necessarily a correct one.
That makes it important to set expectations around:
- When AI is appropriate for a task
- What outputs need to be checked
- Which decisions require human review
- Who remains accountable for the result
Those boundaries will look different depending on the work and the risk involved. Brainstorming with AI, for example, calls for a different level of oversight than using it with sensitive information or consequential decisions.
AI training should cover both capability and limitation. Employees need enough understanding to recognize when an AI system is useful and enough judgment to recognize when its output requires scrutiny.
3. Reskill Employees for What Comes After Automation
When AI frees people from routine work, the next question is how to put that time and talent to better use.
Paul Zikopoulos, VP of Technology & Skills at IBM and a future trends expert, calls his approach “Shift Left to Shift Right.” Use AI to reduce routine, inefficient work so people have more capacity for creative thinking, innovation, and other work that can move the business forward.
For leaders, the important part is planning for that second shift. If AI reduces part of an employee’s workload, don’t stop at the productivity gain.
That could mean developing stronger problem-solving skills, giving someone more responsibility for customer relationships, or involving them in work they previously didn’t have time to tackle.
Zikopoulos also emphasizes that AI innovation isn’t limited to people with technical backgrounds. Give employees opportunities to experiment with AI on real business problems. You may find useful applications for the technology while also identifying people who are ready to take on new kinds of work.
4. Create a Process for Scaling What Works
As AI use grows across your organization, you’ll need to decide what’s worth investing in and what isn’t.
Something that works well for one team may have potential elsewhere. Other applications may be useful in a limited setting and don’t need to go any further.
Jon McNeill, former President of Tesla and COO of Lyft and now CEO of DVx Ventures, looks at these decisions through two lenses, effort versus impact and partner versus own.
When you’re deciding what to scale, consider:
- Is the impact worth the effort? Look at what you’re getting back compared with the time, cost, complexity, and risk involved.
- Do you need to own it? Some AI capabilities may be important enough to build internally. For others, an existing tool or outside partner may make more sense.
It’s also worth revisiting these decisions regularly. What’s working? Could it solve a similar problem somewhere else? Is something taking more time or money than the value it provides?
A regular review can help you put resources behind the AI applications that are working and let go of the ones that aren’t.
5. Test the Assumptions Behind Your Workforce Plan
Every workforce plan makes assumptions about what your organization will need from its people in the years ahead. With technology advancing so quickly, those assumptions are worth checking regularly.
Futurist Amy Webb, founder and CEO of the Future Today Strategy Group, helps organizations challenge what they assume about the future before those assumptions turn into expensive decisions.
Start with a major workforce decision, such as hiring for a role, investing in training, or changing how a team is structured. Write down the assumptions behind that decision. If you’re hiring, which parts of the job do you expect a person will still need to own in three years? If you’re investing in a skill, what could make that skill more or less valuable as technology improves?
Next, consider what could change those assumptions. A new capability, a shift in customer behavior, or a different way of doing the work could point you in another direction.
Doing this before you make a long-term investment can help you catch assumptions that may already be changing and make a workforce decision that gives you more room to adjust.
Find the Right AI or Future of Work Speaker with Leading Authorities
As AI becomes more embedded in how work gets done, leaders are facing bigger questions about what comes next for their workforce. Depending on where your organization is, the conversation may need to focus on redesigning work, responsible AI and governance, reskilling, leadership, or how to turn AI investments into business results.
Leading Authorities works with AI speakers and future-of-work speakers who approach these questions from different perspectives. Our team can help you find an expert whose experience and message fit the workforce challenges your organization is working through.
To learn more or find a speaker for your next event:
- Call us at 855-827-9635
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