Before chasing agentic AI, fix your generative AI adoption problem

From cutting-edge automation of daily tasks, to supporting creativity, the promise of Generative Artificial Intelligence (Gen AI) to revolutionize productivity and innovation is clear.

However, despite organizations investing heavily in Gen AI, with an expected annual growth rate of 36.6 percent from 2023 to 2030,¹ only 0.5-3.5 percent of work hours are spent by employees using these tools.² Further, research shows that over half of companies report no improvement in performance or profitability from their digital transformation efforts over the past five years.

This lack of return on investment (ROI) suggests that the implementation of AI capabilities is not strategic enough. It also indicates that opportunities to maximize employee engagement are being missed.

Is there a smarter way to drive Gen AI adoption within the workforce?

Gen AI in daily life

Whilst adoption levels are low in the business environment, people outside of the workforce are engaging with GenAI tools to enhance their lives. Enthusiasm for Gen AI was clear when AI bot ChatGPT reached an estimated 100 million active monthly users just 2 months from launch, compared to social platform TikTok, which took 9 months to reach the same milestone.³

Personal use cases could be building a holiday plan of activities, getting help with writing emails, or designing invitations for a party. Evidently, something needs to be done differently to replicate this level of personal engagement with Gen AI in the work environment
A different type of tool

A key challenge with Gen AI in the workplace is that implementation is not a ‘set and forget’ activity in the way that many other tools are. For example, with SaaS technologies, employees are trained in standardized ways and are only retrained if there is a major system update.

In contrast, Gen AI tools typically complement other processes, and can be used in countless different ways across different roles. Therefore, training needs to be tailored to each function, and ideally each individual, role so that people can see the use cases and benefits relevant to their own work.
Improving adoption and unlocking capacity

Improving the adoption of Gen AI tools is a commitment that needs to start with the C-Suite, then embraced by leadership, then by employees. However, a reverse cycle is also true – with the need for employees to feel empowered to safely experiment with the tools, and to bring new use cases and understanding back up through the organization. When employees are making the most of Gen AI, leaders can bank that impact by reshaping roles, teams and functions to make the most of the unlocked capacity.
Help from behavioral science

When supporting employees to adopt Gen AI, it is helpful to recognize the role that behavioral science – the study of how humans behave – can play. Gen AI requires people to work as ‘peers’ of the tools, for example, asking the tools what they want done, then explaining how. This requires a change in daily work habits, but the need for change could expose biases such as resistance to change, sensitivity to wasting effort, and fear of the unknown and what this might mean for everyone’s role (see Figure 1).

Due to these inherent biases, sending out a communication that says, “Generative AI is now on your system and ready for use” is not going to make people use it. Likewise, telling people to do a training course on an AI tool, and measuring whether they've done it, is not going to make anyone implement the tool into their daily habits.

Instead, there is a need to develop a change program that specifically communicates to these biases, and is tailored to individuals.

More effective communications

In communications around Gen AI, it is important to address biases such as change resistance or sensitivity to wasting effort. This can be done by highlighting how making small changes with Gen AI could make jobs easier and free-up time. Likewise, addressing the bias of fear could be done by reassuring people that Gen AI is not designed to take over jobs, but is there to improve their experience and support them with the tasks they find less interesting.

It can help to appeal to intrinsic motivations, such as social recognition, a sense of accomplishment, or even the satisfaction of overcoming a challenge. Demonstrating how Gen AI can facilitate personal growth and career advancement could also increase engagement.

Further, it helps to communicate how Gen AI tools make employees even more valuable to the organization, with their increased ability to focus on more strategic, value-adding work.
A unique change management approach

Simply providing workers with access to Gen AI tools is clearly not enough. At KPMG, we can support you with a Gen AI change management approach, underpinned by behavioral-science insights. We do not just focus on the what, such as the choice of tools and training, but the how – how the tools are applied, and the communications used to inspire the human behaviors that drive adoption.

Identifying exactly where AI will create measurable impact

We determine where and how Gen AI is likely to be most effective across the business. By pinpointing areas where it will have a measurable impact, employees see how it addresses specific pain points. We also focus on an adoption journey for employees that inspires and engages them to be intrinsically motivated to change. This helps them overcome biases as it is clear ‘why AI is beneficial to them’. This can lead to guidance about the more strategically meaningful work their freed-up capacity allows.
Augmenting the workforce and building the change muscle to fully harness Gen AI

We look at where the most potential lies to get significant value from Gen AI, which can drive a more personalized approach to adoption, upskilling, and augmenting the workforce. We look at role-specific training, and ensure employees are confident using the tools. We encourage deployment teams to leverage ‘social proofing’, highlighting success stories of AI adoption, as people are more likely to adopt behaviors when they see trusted leaders and peers doing the same. We focus on building ‘habit loops’ by embedding AI tools into daily workflows as the default for certain tasks, as repetition and convenience support new habits.
Reshaping the workforce to realize capacity gains, and refocus workforce energy to grow and innovate

We focus on establishing metrics to measure success, such as time saved, and sharing tangible results to show how Gen AI is enhancing, not threatening roles. We review how this freed-up capacity makes time for more meaningful work, then reshape roles around this new capacity. To get positive behavioral change around AI to stick, we help ensure that there are no contradictory messages from leadership, or in how people are performance managed. We also focus on rewarding employees who embrace Gen AI, leveraging the benefit of positive reinforcement.

In summary

By factoring behavioral science thinking into change management around Gen AI, the difference between the tools sitting unused or being effectively adopted can be significant. With stronger adoption of Gen AI into the business, organizations have a platform to redefine roles, teams, and functions, and to unlock value and growth.