Despite these opportunities, the report shows that only a third of service employees find management communication on AI clear. Only 28 percent see a strong connection between what managers say and what the company actually does.
However, Martin emphasizes that management cannot handle this situation alone. “CIOs play a critical role, but it’s not a problem they can solve alone. Additionally, I wouldn’t say IT created this problem themselves.”
Many companies, the manager continued, took the obvious first step and made the tools available to employees securely and on a large scale. “That was necessary, but not enough,” he explains. The next phase must be much more cross-functional.
CIOs should help establish the technology foundation, governance, data model and measurement systems, Martin said. At the same time, they also played an important role in creating strategic clarity. Employees would need to understand why the company uses AI, where it is intended to create value and how work will change as a result.
The BCG executive noted that CIOs should pay close attention to cognitive load, particularly in technology teams, as these teams are often the heaviest AI users.
“This means they may be most exposed to the mental strain that can come with reviewing results, managing AI tools and constantly adapting to change,” he notes. The greatest gains would be achieved when technology strategy, people strategy and employee experience go hand in hand. If AI remained just an IT project, companies would not fully exploit the value.
New expectations
The abundance of AI activities has another effect: 60 percent of respondents say that the bar for work that is considered “good enough” is now higher.
According to Martin, this is because AI is changing expectations. “If a tool can create an initial draft, summarize research, generate options, or automate a routine task, then ‘good enough’ moves up the value chain,” he explains. “People are now expected to spend less time producing basic results and instead use their judgment more.” He gives examples
- quality control,
- Improving results, making decisions and
- the classification in the respective context.
This could definitely be positive, says Martin, as it makes the work more interesting and valuable. “But it also explains why many employees feel greater mental stress. The remaining work is often more complex.”
Managers need to recognize that AI not only makes people faster, but also changes what peak performance looks like, said the BCG man. This means that companies will have to adapt their training programs, performance expectations and management support accordingly. (mb)
