Navigating the rollout of Gen AI in enterprise

It’s no secret that businesses are turning to generative AI to enhance productivity, efficiency, and scalability. Yet very few could have predicted the speed and scale of adoption – namely that the use of generative AI within business processes would grow by an astonishing 400% in 2023.

This growth becomes even more poignant in the context of increasing pressure on the rollout of generative AI in the UK. Last month, a new report from the Communications and Digital Committee called on the UK government to adopt a more positive vision for AI – with specific references to generative AI – to reap the social and economic benefits and enable the UK to compete in this area globally.

However, many UK businesses are already deep into their generative AI rollout strategies and aligning with the global trend of rapid adoption. With this, leaders are having to navigate unforeseen challenges related to internal ownership and governance. Historically, IT departments would be central to any technological rollout but when it comes to generative AI, the internal driving force is not the team you may expect.

Everyone is automating their work, regardless of technical skill

New research from the Work Automation Index 2024 reveals an unprecedented ‘democratisation’ of generative AI within businesses. Put simply, the hype around generative AI has prompted individuals within organisations to automate their work processes proactively.

As a result, the sheer volume of applications and processes within individual companies is rapidly increasing. Alongside this growth, there is a rise in both the number and variety of automation tools. While each new tool pledges to minimise fragmentation and revolutionise the enterprise, this ‘patchwork’ approach has exacerbated fragmentation. Instead of dismantling existing silos, UK businesses are inadvertently constructing new ones.

Understanding the democratisation of generative AI

The democratisation of generative AI is largely driven by the rise of low-code, no-code technology which has given employees the capabilities and confidence to automate their processes regardless of technical background.

The research found that nearly half (44%) of all automated processes are now built outside of IT. Employees no longer have to wait for the assistance of an IT specialist who would typically need to write lines of code to add a new search field to an internal database. Instead, employees across all departments of the business are empowered to introduce automation themselves.

There is a caveat, however: without a strong system of governance, scaling automation with generative AI can quickly become anarchy instead of a democracy. This is because automated processes with generative AI are growing more complex, requiring more steps than ever before. There will also be mixed levels of sophistication between internal departments, leading to discrepancies in security, scalability, change controls, and compliance which ultimately increases business risk.

This risk is the reason behind IT departments taking on a ‘player-coach role’: 56% of automations are still built by IT personas, but IT is also being tasked with governance and guidance for the 44% handled by other teams within the business.

The value of taking a holistic approach

Whilst generative AI doesn’t follow traditional business patterns of implementation, there are many lessons to be learned from the successful rollout of other technologies. Typically, when organisations approach various types of automation, they start with narrow-scope business challenges and test the benefits and pitfalls before moving forward. With generative AI, there is much less willingness to stagger the rollout, with multiple departments making progress at different speeds all with different needs.

To maximise the potential of generative AI, the CIO, and broader IT team need to become the guiding voice. If the CIO has clear sight of all the various stages of generative AI rolling out across the business, the necessary guidance and parameters around security, scalability, change controls, and compliance can be provided.

For new projects, IT can help the business take a more holistic view and encourage departments to look at the end-to-end processes of adopting AI and automation as opposed to having a short-sighted, task-oriented focus. By prioritising projects which have larger-scale benefits, rather than sporadic experimental use cases, there is huge potential for businesses to get more out of the technology.

Similarly, there are principles around growth, process, and scale that should be followed. These principles apply to automation generally but have relevance for generative AI in particular. For example, the process will be optimised when companies automate end-to-end processes rather than individual tasks. Meanwhile, companies with the right growth mindset will strive to embrace change and challenges in their processes, rather than build rigid, unchanging automations. Finally, companies must also establish the scale mindset; this requires embracing democratisation of data, allowing both business and IT teams to automate.

This new era with generative AI demands holistic leadership and the willingness to dismantle existing silos to pave the way for transformative change. By thinking differently about AI and automation, businesses are better placed to stand out from the competition and tap into their digital transformation journeys.