Think of AI as a dishwasher.

What are the main drivers of successful AI adoption?

In one of my keynotes, I talked about the main drivers of successful AI adoption. All of them center around the human factor. Business leaders who succeed with AI bring people along and eliminate the fear many employees have about AI.

These business leaders also guide employees to embrace AI. They engage them not only in using AI tools and systems, but also in redesigning processes that take full advantage of AI‘s capabilities. Employees then use AI to improve their own workflows.

This trend is growing, according to the recent annual global survey AI at Work from Boston Consulting Group (BCG). The 2026 survey covered close to 12,000 frontline employees, managers, and leaders in more than a dozen markets.

According to BCG, “Compared to 2025, the number of organizations that have graduated to using AI to reshape workflows […] has nearly doubled: 42% versus 22%.”

Why redesigning workflows matters for technology adoption?

Many past technology introductions became successful only when the corresponding workflow was redesigned to take full advantage of the technology.

Take washing dishes for example.

You can create a humanoid robot that replaces a person washing dishes in exactly the same way the person has done it before: physically scrubbing them. Or you can create an enclosed tub that cleans dishes by spraying a mix of water and detergent. Dishwashers became commercially available in the 1950s, although the first designs were created in the 1880s. The dishwasher changed the process of washing dishes, taking full advantage of the technology.

The assembly line was another innovation that changed the production workflows, taking the full advantage of the conveyor belt and mechanized assembly tools.

Refrigeration replaced traditional food preservation methods such as salting or smoking, redesigning the entire food supply chain and reorganizing it around cold storage.

The printing press changed the manual process of copying manuscripts by hand to mass production of texts, making publishing, editing, and distribution scalable.

How is AI reshaping business workflows?

Is this too much about old, although still useful, technologies? How about process redesigns that take full advantage of AI?

In successful application of AI in customer service, processes are redesigned with AI in mind. Since GenAI is not fully capable of addressing all customer queries, customer calls are categorized. The ones where the responses are simple are addressed by AI chatbots while the more complex ones are routed to humans.

With AI in predictive maintenance, technicians no longer service machines on a pre-defined, standard maintenance schedule. Technicians’ workflows are dynamically adjusted based on machines that need to be serviced sooner, prioritized based on the likelihood of their failures.

AI loan underwriting enables fully automated micro-loans to millions of users with no human involvement. The underwriting process is built around AI models that evaluate behavioral data from mobile devices, payments, and browsing history. AI identifies low-risk customers for automated loans while loan requests from higher risk customers are addressed by humans.

AI-automated assembly lines take mass production to another level, especially for plants operating globally. With real-time analytics, AI predicts bottlenecks, triggers quality checks, and dynamically assigns tasks. It proactively reroutes workflows and reduces the need for traditional shift-by-shift hand-overs.

Coming back to the BCG survey, one of their recommendations for AI success aligns with what I recommend to business leaders: Invest in redesigning work end-to-end, not in more tools.

When I advise companies on turning AI ambition into business value, I also bring the focus on the human factor and employee AI adoption:

1️⃣ Provide business leaders clear goals to align priorities
2️⃣ Help employees use AI with appropriate skills and judgment
3️⃣ Answer for everybody the question “What’s in it for me?”