A new workplace study from Cognizant has identified what researchers call the “Activation Gap”: a wide and largely invisible divide between the potential that employees believe AI can bring to their work and the extent to which their jobs allow them to use it.
According to the conclusions of the report “New Frontiers, New Frictions: Mapping the DNA of AI Adoption” – in which employees in both Spain and 23 other countries have been surveyed – the main obstacle to realizing the economic potential of AI lies in transforming employee willingness into effective adoption. Customization, integration, and context engineering can help close this gap.
Productivity improvement that AI can provide
Cognizant researchers estimate that a uniform 5% increase in labor productivity globally could add approximately $6 trillion to global GDP, nearly the equivalent of adding an economy the size of Japan’s. Closing the “activation gap” is a potential way to capture part of that value and promote the subsequent employee salary growth that usually accompanies GDP increases. Additionally, whether workers understand and trust the productivity gains that AI can bring is an early indicator of the likelihood of success.
“Our research reveals that employees are ahead of their companies,” said Ravi Kumar S, CEO of Cognizant. “Predisposition is the most complex aspect of any technological transformation, and we already have that. What lies ahead is the work of contextualization: adapting the tools to the standards, workflows and operational dynamics through which each team performs its tasks. Tools designed for a specific context work, while generic ones stagnate. That is the work we do daily with our clients, and it is the opportunity that any company has before it right now.”
The study also yields the following conclusions:
- Willingness to adopt AI: cFour in five employees say they want to use AI more than their current job allows.
- The human factor: Individual predisposition, that is, the way in which a person relates to technology, risk and the work itself, is approximately six times more decisive in predicting behavior towards AI than the position that the person occupies in the organizational hierarchy.
- Navigators and Stalwarts: 72% of workers are concentrated in these two profiles, making them the segment with the greatest potential for impact. A specific intervention aimed only at these two groups could have an effect on the majority of a company’s workforce. Navigators are employees who are willing to use AI but are held back by organizational barriers; Stalwarts, for their part, need a clear reason and compelling business case to adopt it.
- Tools poorly adapted to needs: Up to 82% of employees say the AI tools they currently have do not meet their needs. 33% of Accelerators – power users who use AI heavily – and Architects – employees who adopt technology more quickly – report that a lack of context and personalization is the main factor limiting their use of AI.
Across all employee profiles, between 72% and 82% say their current AI tools do not meet their needs. Even Precisionists – very active AI users and the most satisfied group in the study – reported a satisfaction level with their tools of just 28%. In other words, in the group that most values their AI tools, there are still approximately three dissatisfied employees for every satisfied employee.
Surya Gummadi, president of Cognizant for the Americas, notes, “Dissatisfaction with AI tools in the workplace is not limited to skeptics or those just starting to use them. It is a virtually universal experience that affects both employees highly engaged in AI and those who are not. We collaborate with our clients to identify and implement the most appropriate AI solutions to drive their business results. Our experience in thousands of implementations, combined with this new research, aims to help us deliver “Large-scale solutions, even in the largest organizations.”
Employee training is uneven
The study also reveals a gap between how AI training is delivered and how it is received by employees. Among Architects, 81% consider their training to be effective and 83% complete it. On the other hand, among Holdouts – the group least inclined to use AI – these figures drop to 56% in terms of effectiveness and 53% in terms of completion. However, the training gap does not fully explain the differences in satisfaction levels.
Architects receive the most effective training and have higher completion rates; However, 87% report turning to unauthorized tools when approved options do not meet their needs. These are, therefore, two different problems: training does not reach everyone equally and, even when it is effective, the available tools still do not satisfy their needs.
A workforce more willing and prepared to work with AI is a fundamental aspect for organizations
Taken together, Cognizant’s findings point to a workforce more willing and prepared to work with AI than many organizations currently believe. Providing employees with access to tools adapted to their context, accompanied by appropriate training, is the clearest way to close the “activation gap” and achieve better real business results through AI.
“For the technology to realize the approximately $6 trillion in potential GDP growth that AI could generate, companies must simultaneously provide context-specific tools to a receptive workforce, while improving their training programs by adapting them to different profiles and increasing their effectiveness to obtain real results,” adds Kumar S.
