New research from IFS, the global cloud enterprise software company, has found that executive and board leadership have ‘bought the AI hype’ but organisations are unable to deliver operationally on expectations.

The new global study of 1,700 senior decision makers, Industrial AI: the new frontier for productivity, innovation and competition, found that the promise of AI is being held back by technology, processes and skills.

Half of respondents remain optimistic that with the right AI strategy, value can be realised in the next two years, and a quarter believe in the next year.

Expectations failing to meet reality

84% of executives anticipate massive organisational benefits from AI, with the top three areas AI is expected to deliver value in being high-impact: product & service innovation, improved internal & external data availability, and cost reductions & margin gains. The hype has become so high that 82% of senior decision-makers acknowledge that there is significant pressure to adopt AI quickly. However, this same group of respondents state that they are concerned that a failure to plan, implement and communicate properly means AI projects will stall in pilot stage.

Many organisations have not prioritised elements of development, nor have the infrastructure required to reap the rewards or the skills to deliver on that promise. The study found that over a third (34%) of businesses had not moved to the cloud. While this is not essential to AI adoption, it is indicative of an unprepared enterprise unlikely to be able to scale AI across their business. According to IFS, a robust Industrial AI strategy requires a potent combination of cloud, data, processes, and skills. 80% of respondents agree that the lack of a strategic approach means they have insufficient skills in-house to successfully adopt AI. This sentiment is seen elsewhere in the research with 43% of respondents rating the quality of AI resources in their business, in terms of human skills, as passable and not where it needs to be.

Christian Pedersen, Chief Product Officer, IFS, commented: “AI is poised to become the most transformational enterprise tool ever seen, but our research reveals that there are still fundamental misunderstandings about how to harness its power within an industrial setting. It is telling that AI is expected to significantly reduce costs and raise margins, but a lack of robust strategy means most businesses are under-skilled and under-prepared to achieve these ambitions. We built IFS.ai specifically with these challenges in mind. AI value simply will not be found in a single AI capability but instead by delivering AI across all products and business processes. This supports customers’ decision cycles and provides the data and AI services required to realise value faster.”

Pedersen continued: “Achieving this at scale needs a clear-eyed strategic focus, including the high-impact use cases specific to their industry, having a cloud-based infrastructure in place which has industrial AI embedded, and investing early in developing the skills needed. Adopting this approach will turn the tide of disillusionment, and deliver the benefits that boards and the C suite are demanding.”

Outlook optimistic but planning needed

The unfortunate reality of the skills gap means that in terms of AI readiness, many businesses are falling behind. IFS found that nearly half of respondents (48%) were most likely to say that they are gathering proposals and were much less likely to have a clear strategy and perceivable results (27%). A fifth of respondents are in the research phase, with uncontrolled tests taking place and a further 5% are lacking a coordinated approach and do not have anything in motion yet. Despite initial challenges, there is still optimism with respondents most likely to feel AI could make a significant difference to their business in 1-2 years (47%), and a further quarter (24%) believe it could be within a year.

In particular, respondents are most optimistic about the impact of AI in smart production and/or service delivery on effectiveness & business and operational management (22%) in the future. One fifth see the biggest impact being on innovation with new products and services (20%), growth & business model decision-making (20%), empowering people and increasing talent retention (19%), and customer experience and customer service (19%).

Action needed on data readiness

To reap these benefits, enterprises need to leverage the most strategic asset they have – their data. The right data volume and quality is critical for the success of AI applications. Respondents recognise how important real-time data is to successful AI projects, with over 4 in 5 (86%) stating this. Yet despite this recognition, less than a quarter (23%) of respondents have completed their data foundation with it supporting both data-driven business decision making and real time response to changes, suggesting that more work needs to be done to get data AI ready. Moreover, under half (43%) of respondents have majority structured data, with some unstructured.

Pedersen commented: “The lack of maturity at the data foundation layer needs to be addressed as part of an overall AI strategy, otherwise AI simply will never be the magic bullet that can turbocharge the enterprise. Clearly enterprises need support on data management and migration. While AI is seen as a shiny new tool that will revolutionise business, like all technology, it is never that simple. The power of Industrial AI is that it can touch all facets of a business from product innovation and customer experience to productivity and ESG. Its potential is massive if executives and organisations can combine vision, strategy, technology and skills. Now is the time to step back, take stock, and build a true Industrial AI plan and turn the hype into reality.”