AI transformation only works if everyone is in, and that includes you. Employees who sit out are making a bad career decision, and companies that don’t actively work to drive buy-in and participation don’t get transformed.
Companies are spending billions on AI transformation. Most of the money goes to platforms, licenses, and integration partners. Buying the solution is part of the battle, but I’d argue it’s far less than half of it.
The rest of the battle takes place on every desk and in every team meeting. Do people buy in? Do they use the solution? Do they change the way they work? A transformation is the sum of employees’ answers to those questions. Success or failure comes down to your people. And you.
Where investment pays off
The 2025 MIT NANDA report found that 95% of enterprise generative AI pilots produced no measurable return on the P&L, despite $30 to $40 billion in collective enterprise investment. The part almost nobody quoted is more interesting. The researchers searched for the primary cause of failure, and it wasn’t:
- Model quality
- Regulation
- Infrastructure
- Shortage of AI talent
What killed the pilots was that the systems didn’t fit the way people already worked and didn’t learn anything from being used. Companies that led with workflow fit deployed at roughly twice the rate.
McKinsey’s State of AI 2025 survey reached a similar conclusion. 88% of organizations reported using AI regularly in at least one function. Just 6% saw meaningful EBIT impact. The firms in that 6% are close to three times more likely to say they fundamentally redesigned individual workflows.
We need to understand that buying a platform is not enough. People have to be brought along with a process and toolset that encourage use, build trust, and get better as more people use them.
Some companies back away from the human aspects of AI transformation because they seem more complex than simply writing a check. Many also fear that employees will resist AI reflexively. Some vendors minimize the need for adoption, training, and trust, which compounds the issue by encouraging a false narrative.
Your employees are already using AI
In reality, many employees already use unsanctioned AI on their own. Many senior leaders underestimate the extent to which their teams are already using AI in their work.
McKinsey’s 2025 Superagency in the Workplace study surveyed 118 C-suite leaders and 3,002 US employees. Leaders estimated that 4% of their people use generative AI for at least 30% of their daily work. The employees put it at 13%. Asked to look a year out, 20% of leaders expected the workforce to reach that level of use, while 47% of employees expected it of themselves.
Source: McKinsey, “Superagency in the workplace: Empowering people to unlock AI’s full potential at work”
Individual transformation is already underway. It’s happening in the shadows, on personal accounts, with none of it accumulating into something the company owns or can build on. People adopt a tool when it solves a problem. They don’t adopt because of a memo.
What people say they need
The same McKinsey study asked employees what would get them using AI more. The results:
- 48% said formal training
- 45% said integration into the workflow they already have
- 41% said access to the tools at all
- 40% said incentives for using them
- 22% said they get no support for building the skill
Another critical finding: 71% said they trust their employer to deploy AI responsibly, which is higher than their stated trust in universities, tech companies, or startups. That means that fears about employee resistance are overwrought. Paired with the knowledge of how important the human aspects of AI adoption are, companies must rebalance their investment and attention.
Employees know AI knowledge is important
Postings that ask for AI skills grew about 69% year over year while the broader job market grew 9%. PwC’s 2026 Global AI Jobs Barometer puts the average wage premium for workers with AI skills at 62%, up from 57% in 2025. While most employees will not have read the study, they know the reality instinctively.
Savvy employees understand that AI skills are key to their own marketability. BCG’s 2026 AI at Work study found that 74% of frontline workers now use AI in their work, and 42% say it saves them a day or more per week. More than two-thirds say that AI has taken over their simpler tasks, freeing them up for more complex work.
72% of respondents say the skills expected of them have changed. Only 36% believe they’ve been given enough training to meet the new expectation. Communication isn’t landing either. Just a third of frontline employees call leadership’s messaging on AI clear, and only 28% see a strong connection between what leaders say and what the organization does.
Looking at this data, it’s easy to argue that most employees want to understand how to work differently, but that companies aren’t doing enough to help them do it.
Leadership strategies for AI transformation
Leaders must make adopting AI deliver value for each member of the team. That means:
- Articulating a strategy that clarifies the roles of AI and people
- Choosing a vendor that designs for adoption, trust, and company ownership of the intelligence
- Involving your people in choosing the AI projects that should come first
- Choosing solutions that frontline people use directly
- Putting tools inside the workflows people already use
- Providing real training, with explicit permission to change how the work gets done
For the employees, the way forward is just as clear. They must embrace the technology and look for ways to use it so they can deliver more value. Reflexive resistance to AI condemns them to becoming less relevant in the workforce. Top performers understand this. They realize that adaptability is essential and will likely lead to more interesting and fulfilling work.
More information on AI and people
At RapidCanvas, our focus is on helping companies deploy AI that delivers real business value in weeks, not months. Our Hybrid Approach™ focuses on solving real, tangible problems with tools that are tailored to your workflows and existing tech stack. We create solutions in partnership with your people that they can use themselves with natural language, and include real training as part of each initiative. Most solutions deliver substantive ROI in 6–12 weeks.
If you’d like to discuss the role that people play in improving your AI roadmap, get in touch for a consultation. You can also visit our website to read dozens of case studies and examine verified customer reviews on G2.
