Democratising AI the Right Way: How to Ensure Automation Results in Financial Gain 

By Carter Busse, CIO, Workato 

Generative AI is no longer just emerging technology; it has fully embedded itself in mainstream discourse. Formerly confined to the technical discussions of IT teams or executives’ decision-making, nearly everyone in the workplace is now considering whether they can embrace AI. 

The promise of great rewards led to the use of AI in the workplace increasing by 400%(https://www.workato.com/work-automation-index) last year. From cost savings to enhanced productivity, it has been one of the most hyped technologies of the past few decades. However, implementing automation via AI does not guarantee business benefits. Rapid adoption can lead to unforeseen challenges, and organisations must then iron out the issues caused by a lack of governance or holistic oversight before they can think about reaping the rewards. 

Gen AI automation for one and for all 

Fresh findings from the Work Automation Index 2024 uncover an unparalleled ‘democratisation’ of generative AI across enterprises. This means that the buzz surrounding generative AI has spurred many employees to take the initiative by automating their workflows. Different departments, including finance, are experimenting with AI to drive efficiencies. For example, many manual financial processes involving large databases like Know Your Customer (KYC) and Anti-Money Laundering (AML) can be automated, saving time for the employee. 

With a growing trend for rapid adoption, the sheer abundance of applications and AI processes within individual companies is increasing quickly. Accompanying this surge is an increase in both the quantity and diversity of automation tools. While each tool will promise to mitigate fragmentation and transform the enterprise, this ‘patchwork’ methodology has only worsened the fragmentation issue. Rather than reducing silos, UK businesses are unknowingly creating new ones. 

The pros and cons of democratised AI
 
The democratisation of generative AI is closely connected to the growth of low-code and no-code technology, granting employees the capabilities and confidence to automate their workflows with minimal reliance on IT support. Remarkably, Workato’s study reveals that nearly half (44%) of all automated processes are devised outside of IT. Gone are the days of employees waiting for an IT specialist, who would traditionally labour over hundreds of lines of code to integrate a new search field into an internal database. Instead, employees spanning all departments across an organisation, from finance to customer service, are now readily empowered to implement automation.
 
However, there’s a caveat: without a strong governance system, the expansion of automation with generative AI can swiftly devolve into anarchy rather than democracy. This is because automated processes leveraging generative AI, particularly financial processes, are growing increasingly complex, demanding more steps than before. Furthermore, there will inevitably be varying levels of sophistication among internal departments, leading to disparities in security, scalability, change controls, and compliance, consequently heightening business risks.
 
It is this apprehension around the risk that results in IT departments taking on a ‘player-coach role’ in various departments within the business. While 56% of automations are still orchestrated by IT personnel, IT is also tasked with the oversight and guidance for the 44% managed by other teams within the organisation, such as the finance department.
 
End-to-end transformation drives results 

While generative AI does not adhere to the conventional adoption patterns of other game-changing technologies in the past, there are insights we can ‘borrow’ from a range of industries to create a robust strategy for success. 

This starts with reconsidering the approach to generative AI from the very beginning. Typically, when organisations embark on automation initiatives, they begin by addressing specific, narrowly-defined business challenges, assessing both the advantages and drawbacks before proceeding further. However, with generative AI, there’s considerably less inclination to patiently stagger the rollout, as multiple departments advance at varying paces simultaneously. 

For the finance department to properly leverage generative AI’s potential, it is imperative that they only prioritise projects with broader scale benefits, working closely with the IT team on the company’s goals. The IT team can offer essential guidance and establish parameters concerning security, scalability, change controls, and compliance – something which is critical for a department handling such sensitive data. IT can also assist the team in adopting a more holistic approach, encouraging finance employees to examine the end-to-end processes of integrating AI and automation, rather than adopting a narrow, task-oriented focus. For the finance team, this will help to prevent wasted time in the ‘experimental’ stage by focusing efforts on implementations that will create meaningful business impact and minimising risk. 

By thinking holistically about generative AI and ensuring considered leadership and governance, the finance team will be well-positioned to benefit from the democratisation of AI in 2024 and beyond. When well thought through, generative AI truly can transform a business in the long term, increasing productivity and ultimately revenue.  

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