It can be hard for business and technology leaders to avoid conflating AI and digital transformation. But the fact is they are not the same thing.
McKinsey describes digital transformation as the rewiring of an organisation “with the goal of creating value by continuously deploying tech at scale. A clear digital transformation strategy focused on specific domains and enabled by a set of specific capabilities is critical for organizations to not only compete but survive.”
Meanwhile, it’s becoming clear that many “AI” projects aren’t delivering on their objectives or fail to move to production. This wastes investment without any meaningful return and hampers broader transformation efforts.
The challenge for CIOs and their business counterparts is to maintain focus on their digital transformation goals while identifying where generative AI (genAI) can truly help achieve them, while being aware of the technology’s limits.
For example, the use of genAI to generate code is now widespread. This can potentially speed up digital transformation projects where existing applications must be refactored, or new applications or modules produced.
But it is also clear that this does not remove the need for code testing to review or solve the challenges of deployment. Leaders need to consider how they can automate these elements of the software life cycle too, while ensuring human expertise is used efficiently.
More broadly, digital transformation often aims to break down the silos which trap information within organisations. GenAI can be deployed as part of this process and accelerate the extraction of value.
For example, genAI tools can be used to hoover up disparate data sources and they excel at highlighting relationships embedded in the information that humans and other tools might struggle to surface. This can be used to identify ways to streamline processes or even suggest new business opportunities.
Both these examples highlight how genAI can be used to support broader project planning tasks that underpin meaningful digital transformation.
A successful digital transformation depends on clear communication across multiple stakeholders. Projects also generate a vast amount of data information, which must be continuously analysed, digested and shared across those stakeholders.
The technology has a clear role in producing documentation as well as summaries of meetings. And it can be used to serve up and distribute that information, for example through an internal chatbot which can respond to questions from stakeholders and employees.
But it can also be used to analyse that blizzard of data a project generates. This can help leaders spot otherwise buried relationships or potential dependencies and bottlenecks, across domains, that could throw individual projects or the entire transformation effort off track.
All of this requires enterprise-grade governance and security, integrated AI and data management tooling and resilient, scalable underlying infrastructure. These strategies should be part of any credible digital transformation strategy.
It’s important to be clear what the real aim of digital transformation is. And simply implementing artificial intelligence will rarely be the main objective.
However, when technology leaders are clear what their objectives are, genAI can help them navigate the multiple steps they will need to take to reach their transformation goals.
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