Businesses should pursue widespread automation while ensuring the foundations are in place for GenAI deployment

The past year has seen a rapid acceleration in the rate of adoption of Generative AI (GenAI) solutions. McKinsey’s ‘State of AI in early 2024’ report revealed that the number of organisations that regularly use GenAI has doubled within the past year, with this figure now at 65%.

However, despite the growing popularity and wholesale integration of this technology, companies that rush to implement GenAI to maintain pace with rivals could see unreliable solutions hinder, rather than improve, business performance.

According to Yohan Lobo, Senior Industry Solutions Manager at M-Files, organisations should ensure the necessary building blocks are put in place before GenAI takes up a central role in business processes.

Yohan said: “After the meteoric rise of this technology, we’re seeing people begin to question whether GenAI solutions truly deserve the level of hype and attention they have received over the past two years. While there is certainly an inflated sense of what can be achieved with GenAI, there are still a number of tangible use cases that can add genuine value to businesses across industries.

“Summarising documents, creating content from scratch and even performing translations are all ways that GenAI solutions can be deployed to drive improvements in efficiency. A GenAI strategy that respects security and compliance policies and allows businesses to leverage their data to its full potential can yield enviable results, improving the experience of both employees and customers in the process.

“Where issues arise is when management teams are over-eager and rush into GenAI implementation. Any effective AI strategy should be built on a foundation of structured data that is searchable and organised using metadata, as this is the only way the outputs of a GenAI solution can be fully trusted.

“Getting ‘AI ready’ by conducting a thorough data audit and ensuring that the business has an extensive and reliable store of internal data that its GenAI tool can collate responses from is essential. Any GenAI solutions that are dependent on external information to provide answers simply can’t be trusted – a lack of understanding of where data is coming from is the most common pitfall of GenAI deployment.”

Alongside the development of GenAI, it is crucial that organisations continue to invest in technology that automates processes.

Yohan continued: “With such intense global interest in GenAI and how this technology can be utilised it’s easy to become blinkered, but there are a whole host of alternative ways of improving efficiency businesses should consider.

“For example, automated systems can handle large volumes of work without fatigue, enabling organisations to scale operations more effectively, and perform repetitive and time-consuming tasks, freeing up employees to take on more strategic and creative work. Greater automation also means less manual error, with businesses benefiting from improved security and a better experience overall for the end customer.”

Yohan concluded: “Once organisations have tended to their internal data and made sure that it is properly ordered and maintained can they deliver a GenAI strategy with confidence. Balancing this with automation that ensures routine tasks are handled efficiently, accurately, and consistently is a clear recipe for success moving forward.”