As employees struggle to integrate AI into their work, many managers are asking “Where do I even begin with AI integration?” The answer isn’t in chasing the latest LLM or proving AI competency to clients; AI transformation starts with motivating people first.
Think about this moment as similar to computer adoption in the ‘90s: companies that were the first in their fields to effectively integrate this technology left their competitors in the dust.
3 Tips to Incentivize AI Adoption
- Incentivize every employee with innovation payouts.
- Install guardrails, not speed bumps
- Lead by example
However, dropping ChatGPT into an organization and telling employees “Go be more productive” is like dumping computers on desks in the ‘90s and expecting Excel dashboards the next day. It took people and workplaces decades to adopt computers. Today, AI is already sitting on our desks, though many employees don’t understand how to begin working with it.
To accelerate AI adoption, managers must meet employees where they are, encouraging workers through various incentives to explore and adopt AI, safely removing barriers to experimentation, and leading by example.
3 Tips to Encourage Your Team to Adopt AI
Let’s be blunt: the working world has already changed. Everyone doing computer work will need a new baseline of AI literacy in:
- Tool proficiency: Using AI as easily as email or spreadsheets; fluidly, daily and without ceremony.
- Risk fluency: Knowing what these tools get wrong, where they expose sensitive information, and how to spot dangerous outputs.
- Agent collaboration: Understanding how to delegate, supervise, and refine work done autonomously by AI systems.
For executives, add to this list “leadership playbooks,” since most are expected to lead AI transformations without ever having run one.
This literacy will not be built through self-directed study but by carefully incentivized internal motivation frameworks.
1. Incentivize Every Employee
Perhaps one of the biggest barriers to AI adoption among employees is the concern that it’s going to replace their jobs. Headlines are rife with optimization layoffs and prognostications that AI will replace jobs.
That’s why the most effective way a company can change that narrative and spur AI adoption is through innovation payouts: monetary incentives for employees of every level, offering a portion of the cost savings from AI-driven efficiencies they personally discover and implement.
Imagine this program taking hold at a mid-sized regional bank. The incentive structure spurs a financial analyst to automate quarterly variance analysis with AI, turning a task that would take 20 hours into one that takes only four. If we assume the financial analyst is paid $70/hour, over the next four quarters this time reduction would save the bank $4,500. Rather than pocketing the savings, the bank shares 25 percent with the analyst as a $1,125 bonus, while reinvesting the rest in AI training. The result is both a faster closing of the books and clear incentives for the bank’s employees to keep experimenting with AI.
Successful real-world analogues like the Dana Corporations’s “gainsharing” program prove AI innovation payout programs could be effective.
Second, merit increases can help break through to workers that say they simply don’t have enough time for AI. Employees only have an average of 24 minutes per week to dedicate to learning, according to a Deloitte study, so adding a monetary incentive can help them prioritize the limited time they do have.
Beyond encouraging routine AI education, tying AI mastery to advancement can further incentivize adoption. Managers can take inspiration from Amazon’s RBKS unit, which requires employees to show AI usage with measurable results to qualify for a promotion.
Companies see the most productivity gains with AI when humans are in the loop. Rewarding employees to find new use-cases for AI or to master it is a great way to encourage them to both prioritize AI adoption and offer a tangible benefit for doing so. It’s a win-win for the company and the employees.
2. Install Guardrails, Not Speed Bumps
Once employees are incentivized to act on AI, managers should ensure they can use it safely without being overly restricted. If these factors are out of balance, employees will use AI in secret out of concern they’re doing something wrong.
Make AI safe to try by providing workers with clear policies on what is in and out of bounds, lists of vetted tools and those that should be avoided, and data principles that defines where personal identifying information lives and content they’re allowed to paste into AI.
Ensure any restriction feels less like red tape and more like guardrails on a racetrack, so employees know where they can “floor it” and where they need to slow down for an upcoming turn.
3. Lead By Example
Employees lend most credence to what managers do, not what they say. If AI is a strategic priority, then managers must communicate how they are using it and how it will affect the organization.
Managers should visibly demonstrate AI use across their own work and integrate it into how they set expectations for teams as well as where they allocate time, budget, and headcount. They can also design hiring and promotions to prioritize AI.
They must also build a culture where people who find gains are celebrated, not sidelined. Each organization has a few early adopters of AI so allow them to be accelerants for the entire company. Give these superstars ample time, access, and autonomy to use AI tools and ensure they’re cross-functional, not siloed. Reward visible wins along the way and encourage them to share failures that taught something useful.
Take caution, however, to avoid mistaking enthusiasm for expertise. Instead, pair enablement with lightweight quality assurance.
If automation will change roles, leaders must show how displaced capacity leads to new value creation, not layoffs. Perhaps most important: leaders should design AI adoption frameworks for failure. Experiment, test, and iterate because nobody will get AI right the first time.
Invest in Your Employees to Adopt AI
Company-wide tech transformation is possible; just look at AT&T’s Future Ready program, which invested $1B in worker reskilling following the realization that half of its 250,000 employees were working in jobs that would become technologically obsolete. This program retrained 100,000 workers for high-demand roles like cloud computing, data analytics, and cybersecurity, helping AT&T internally fill roles essential to remaining competitive in the next technological era.
AT&T’s reskilling initiative shows that AI transformation will be a people-first challenge, and “people” also includes you. Discover what’s holding back your own AI adoption by asking: “Do I truly understand what AI can do today?” and “What is still getting in the way of me using it more?”
The companies that thrive won’t be the ones boasting the best tools but those who have motivated and trained the entirety of their workforce to collaborate with AI. This journey is about motivating people and it starts with you.
