It’s budgeting season, and Artificial Intelligence (AI) is topping the “to buy” list in many procurement conversations.
Organizations are investing serious money in onboarding new tools, platforms and capabilities – and the fear of falling behind is prompting teams to race headfirst into buying and deploying powerful new agentic systems.
But deploying AI is not the same as getting value from it. According to a recent report on the state of digital adoption from WalkMe, 77% of executives say adoption is the real challenge when implementing AI.
Buying technology is just step one. People still need to understand how the tool changes their work, when to rely on it, when to question it, and who’s accountable when things go wrong. WalkMe’s research also estimates that companies lose $72 million per year from employee time lost to friction and $142 million in total to digital inefficiency. Those are staggering numbers.
All too often, organizations treat AI as just a technology decision. Select a tool, deploy it, then train employees, and measure use. That’s backwards thinking. Treating AI as a technology purchase is like buying a gym membership and expecting to get fit because the card is in your wallet. The membership gives you access, but results come from understanding how to use the equipment, building routines, tracking progress and changing habits. Purchasing the technology creates the opportunity for value, but adoption determines whether that value is ever realized. That’s why it’s essential to incorporate a strong employee engagement and change management strategy from the outset. Anticipate how they will use the tool and create guidelines and guardrails before challenges arise – not after.
AI changes how people work. It impacts their authority, confidence, and accountability. If employees don’t understand why it is being introduced, what its potential and limitations are, when to trust it and when to challenge it, the organization hasn’t really adopted AI. They’ve just made it available.
Without a strategic approach, no matter how fancy an AI promise may be, the outcome is guaranteed to be a letdown – low utilization, inconsistent use, workarounds that compromise integrity, and an investment that struggles to show real business value.
The problem isn’t that people are resistant to new technology – enough organizations have successfully adopted and integrated other tools into their operations. The challenge with AI is its broad potential for misuse and a lack of clarity around how (and how not) to use it. People need practical questions answered, like:
- What can the AI do, and where are its limits?
- What am I going to be responsible for?
- When should I step in and be the human in the loop?
- What information is appropriate to share with it?
- How will my decisions be valued along with its recommendations?
This is why leaders need to step beyond product rollout and into role design.
The critical part of AI adoption is defining the relationship between people and technology before people use it. An AI-powered booking tool, for example, needs more than just a simple launch campaign. Travelers, travel managers, support teams, program leaders all need to know what the tool can do on its own, where human oversight rules are essential, and how exceptions can be handled before they start using it.
Training attendance, email opens, and issued licenses are only the first metrics to measure in a program kickoff. Successful adoption happens when teams use AI tools safely and consistently, integrate them into their work, and start to make better decisions.
Here are six things business leaders need before an AI launch:
- A readiness assessment to understand the context for bringing in the tool. Is the team prepared for a change? Is the underlying data good enough? Are the right stakeholders on board? What concerns need to be addressed first?
- Clear human oversights and rules for escalation. Where can the technology act independently? What needs human review? Who is going to be accountable for the output? Teams should never have a doubt where ownership lies and how to address challenges.
- Pilot groups and feedback loops. Every rollout needs some settling into the “new normal.” Piloting systems allow teams to address unclear instructions and friction points before a widespread rollout.
- Employee champions. Who are the influencers within the organization that can support the system coming online? Who will not only be able to promote it effectively, but also test it, question it, and bring real employee feedback to the table?
- Training and a communication plan based on real employee questions. Training should address the lived experience of the people who are going to use the technology. Employees need to understand how new technologies impact their specific responsibilities or workflows, and why. The time to think about a change management campaign and ongoing communications support is before a tool is deployed, not after.
- Measurement that links to business results. If AI was only valued for generating activity, every rollout would be a success. We need to ask a more important question: Is the system achieving its intended goals or solving the challenges it was implemented to address? Organizations should be measuring whether AI is helping make better decisions, creating more consistency, reducing risk, and improving employee experience and business performance – not just if people are using it.
At Advito, we believe that human accountability is absolutely essential for responsible use of AI. That accountability only works when employees have a smart structure to work within, and the confidence and authority to act upon it.
The value of this approach is not theoretical. Within our own organization, some of the most successful AI initiatives have been supported by employee champions who were curious, engaged and willing to experiment. Their role was not to promote AI blindly, but to challenge assumptions, share lessons learned and help colleagues understand where the technology added value. Combined with practical use cases like automated meeting transcription, action tracking and content drafting, this created momentum that training programs alone could not achieve. People adopted AI because they could see how it improved the way they worked.
That’s the thinking behind “AI Gateway,” our new human-centered solution for organizations serious about turning their agentic investments into successful adoption. It combines readiness assessments, road-mapping and strategy, governance controls and behavior change management, because we know that it is the synergy of all these functions that yields real success.
AI can be a powerful, positive force for organizations and the people they serve, but only if employees use it and trust it. Trust comes from transparency, guidance, human oversight and experience.
Ultimately, the strongest signal of AI success won’t be whether a company has bought a platform. It’ll be whether it’s designed the right system for people to use it effectively.
