What the cloud era can teach us about GenAI adoption

GenAI adoption: Group of workers looking at laptops in a conference room

Generative AI (GenAI) has rapidly gained momentum over the past couple of years, leaving business leaders staring down the barrel of a huge technological change. We all want to know how changes like this will affect us and what our next steps should be. Fortunately, we’ve been in this position before.

When cloud computing first took off in the mid 2000s, it was met with hesitancy and fear. Today, it’s rare to encounter a business leader who doesn’t rely on it. The parallels between the adoption of cloud computing and GenAI offer key learnings as we move towards widespread adoption of the latter.

1. GenAI is an operational investment

Much like the cloud, GenAI is positioned to affect every type of organisation. The technology can be adopted by anyone—from the largest companies in the world to the smallest independent businesses. In fact, McKinsey estimates GenAI is poised to increase the impact of all AI by 15% to 40%, adding up to USD 4.4 trillion annually.

The cloud era allowed organisations to transition from capital-intensive projects to more sustainable operational investments. GenAI is poised to replicate this trend, advocating for a similar shift from CapEx to OpEx that suits all types of business.

This means there’s potential to use GenAI for business benefit, no matter what the organisation looks like. Those who embrace this accessible approach to technology will likely reap the benefits of enhanced productivity, efficient working, and lower running costs.

2. GenAI requires security and data management

GenAI needs a huge amount of data input to work successfully. Organisations are still in the initial stages of figuring out the associated security implications of feeding their data into AI solutions.

In the early days of cloud adoption, organisations faced the same concerns. Leaders had to work out how to demonstrate that the cloud was reliable enough to encourage organisations to supply it with large amounts of data, as well as whom to partner with to ensure its security. The resulting feeling was a sense of uncertainty or ambiguity—which is what many leaders feel about GenAI today.

Navigating data-powered solutions securely comes with high stakes. The importance of data has taken on new significance as consumers become more aware of how organisations manage—and use—their data.

According to a 2022 survey from Statista, 70% of EU consumers have concerns that organisations could use their personal data for purposes other than intended. This is backed up by ServiceNow and Opinium research, which shows data security is a top priority for consumers in EMEA when choosing to spend with a business.

As we unravel the complexities of GenAI adoption, the lessons from the cloud era remind us to prioritise data management and security. It’s about acknowledging the immense opportunities at stake while being acutely aware of the potentially greater penalties for organisations that get it wrong.

3. There’s no one-size-fits-all GenAI strategy

The business benefits of AI are available to all types of organisations, providing they make appropriate investments. Becoming an early adopter of GenAI requires paying a premium to hire people well versed in the technology, whether they be data scientists, analysts, or engineers.

According to Oxford University research, since 2015, there’s been a five-fold increase in the demand for AI-related skills in the global workforce. The takeaway for organisations is simple: If you don’t understand your data lifecycle or the regulations around AI, you need to hire people who do.

For organisations hesitant to become early adopters of GenAI, it’s advisable to hold off and pay attention to the learnings of those that embrace it. Once these early adopters have made the necessary investments, we’ll start to see a more commonly accepted way of managing data in large language models.

4. GenAI should be seen as a long-term value-add

Any transformative technology—be it cloud, GenAI, or something else—follows a common pattern. We can think of it as a typical hype cycle that consists of anticipation, early adoption, a cautious middle ground, and eventually laggards who trail slightly behind.

GenAI still sits in the very early stages of that cycle. Dell research shows just 44% of organisations are currently in the early or mid stages of GenAI adoption, meaning most have yet to make any real headway.

There’s also a lot of misinformation surrounding the subject. Here, we can draw another parallel: When the cloud first gained traction, leaders believed it would be less cost-effective, less secure, and less reliable than traditional IT infrastructure.

The only real way to resolve this issue and move through the cycle when it comes to GenAI is to allow it to happen naturally. We’re beginning to see what GenAI looks like for organisations in practical terms. Emerging use cases include:

GenAI adoption is a journey. At ServiceNow, we encourage organisations to take it at their own pace and to streamline a base layer of AI or automation first.

The mature capabilities of GenAI—predictive intelligence, statistical analysis, natural language understanding, to name a few—are game changing. It’s important to work out exactly how technology can support a use case within your business and go from there.

Find out more about how ServiceNow can help your organisation put GenAI to work.