From AI excitement to alignment: Making digital adoption work

Artificial intelligence (AI) has been the topic of discussion among leadership teams. Many will be familiar with ChatGPT. In early 2023, it became the fastest-growing web tool in history, having surpassed 100 million active users in two months. With such popularity, it was only a matter of time before businesses wanted the latest AI capability.

The PEX Report 2025 found that 58 percent of businesses are exploring how AI can improve operations. Discussions about acquiring new capabilities are on the table. However, acquiring something is not the same as adopting it. Adoption is about embedding technology into the company.

Digital adoption cannot be sustained by hype. Any new digital technology, AI or not, should align with the current capabilities of your organization. Here are a few tips to consider in your digital adoption strategy. 

Identify what customers value

Digital adoption should align with business needs. Transformation leaders should look past the product features and ask “how does this solve the employee or customer pain point?” The answer is not as straightforward in practice.

Suppose a financial services company wants to undergo a digital transformation project and automate their repetitive tasks. The transformation should begin with the customers. The B2B customers understand that risk audits can be repetitive, but they appreciate the assurance the financial firm provides them. The reason why B2B chooses this financial services firm over another is due to trust. Automating manual tasks might solve the problem of efficiency, but in doing so, it can erode the trust of its customers. The trust factor was a big reason why its customers chose that financial service firm in the first place.

A survey by Aveni and YouGOV revealed a stark contrast between age generations. In the findings, 83 percent of respondents in the 25-34 age range felt comfortable using AI-assisted financial advice compared to 33 percent of respondents over 55. Digital transformation should still begin from the pain points of customer groups and their needs, rather than the idea of cutting efficiencies and costs. The consequence is that teams develop a solution that does not address the problem. The outcome is that employees or customers abandon the technology.

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Learn how the company makes decisions

Software can exist in a larger company without a strategic plan behind it. They may be legacy technology or infrastructure inherited from previous employees. You can gain insight into how a company adopts these tools by looking into the decisions. For example, professional services have partnerships to support their advisory work. The question is “how did the customer software make its way to the company?” In other words, “why did they make that decision?” If the software was acquired from a startup, then it’s worth asking “who’s benefiting from this new capability?”

It’s typical to find that acquisitions have been made years ago, but employees are not using them and instead prefer to fill out forms manually. Even in a sector with high-volume processing, such as the payment sector, 90 percent of firms still rely on spreadsheets. 

Despite these practices appearing outdated, our expectations for “modern” should not be based on AI. Hype can act as a yardstick to chart a new roadmap and motivate effective performance However, our thinking around digital adoption should also be grounded in the present.

In Cisco’s AI Readiness Index, only 13 percent of sampled companies reported that they had the infrastructure to support AI initiatives. This area of readiness concerned the data centers and workforce. There are good reasons why some departments are slower to adopt AI than others. What’s more important is gaining perspective of the other side. For instance, some may view technology as an opportunity whereas others in the company view it as a risk. 

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Don’t ignore the slower adopters

We’ve all heard about the adoption curve. It was initially intended for strategy but has been increasingly applied to technology and innovation. In Geoffrey Moore’s product adoption curve (below), the early adopters sit on one end and the late adopters on the other. Even though the curve is normally spread out, most managers take this curve diagram as inspiration to convert the laggards into early adopters and innovators. Unless a company has screened for this ability, don’t expect them to become champions overnight or that “Gen Z” will embrace your AI initiatives. They still exist and are here to stay. Your digital adoption strategy should focus on the pain points of both early and slow adopters, covering the full spectrum of users. 

Source: Positioning - Geoffrey Moore

It’s normal for busy managers to lose sight of the current problem they are solving. At times, change managers can view the lack of adoption as a chance to amplify their personality. They push the solution harder to those who champion their cause. This would appeal to innovators, who crave fresh and novel ideas.

However, the adoption gap would still remain because it misses out on the slower adopters who happen to be the majority. The early majority, the late majority and the laggards are satisfied with less novelty. 

Digital adoption is about people and processes

Digital adoption is about people and processes as much as new technology such as AI. There are business process management (BPM) frameworks that go into depth and include sponsorship, governance, excellence centers and human affairs. More importantly, managers should begin preparing and laying the groundwork before such frameworks. Successful adoption begins with understanding where the organization’s current technology and capabilities are at, and whether they align with business needs. 

Acquiring AI, or any new technology, does not lead to its adoption. It must still solve a customer or employee pain points. Asking “what problem does this solve?” can help identify the core value that the initiative can bring the business. 

Software already adopted by teams may have been inherited. Understanding how an enterprise makes decisions is an important step in planning the next digital transformation journey.

The newness effect is not enough to sustain adoption. It is useful to take another look at the product adoption curve to create a plan to capture early and late adopters. Whether AI is new or old is not as important as aligning with the company’s current capabilities and it’s adoption potential. 

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