Management Buys into AI Hype, Yet Organizational Readiness Lags: IFS

Management Buys into AI Hype, Yet Organizational Readiness Lags: IFS

IFS-commissioned research shows value creation lags behind AI promise without the right planning and application.

New research from IFS, the global cloud enterprise software company, has found that executive and board leadership have ‘bought the AI hype,’ but organizations cannot 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 technology, processes, and skills are holding back the promise of AI. Half of respondents remain optimistic that with the right AI strategy, value can be realized in the next two years, and a quarter believe in the next year.

Expectations failing to meet reality

84% of executives anticipate massive organizational 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 states that they are concerned that a failure to plan, implement, and communicate properly means AI projects will stall in the pilot stage.

Many organizations have not prioritized development elements, 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 its 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 adopt AI successfully. This sentiment is seen elsewhere in the research, with 43% of respondents rating the quality of AI resources in their business, regarding 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 harnessing its power within an industrial setting. It is telling that AI is expected to reduce costs and raise margins significantly. Still, a lack of robust strategy means most businesses are under-skilled and under-prepared to achieve these ambitions. We built specifically with these challenges in mind. AI value will not simply be found in a single AI capability but by delivering AI across all products and business processes. This supports customers’ decision cycles and provides the data and AI services required to realize 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 with 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 demand.”

The outlook is optimistic, but planning is needed

The unfortunate reality of the skills gap means that many businesses are falling behind in AI readiness. IFS found that nearly half of respondents (48%) were most likely to say they were 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% lack a coordinated approach and do not have anything in motion yet. Despite initial challenges, there is still optimism, with respondents most likely feeling 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 sees 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%).

Also Read: How Predictive AI is Transforming the Retail Industry

Action needed on data readiness

To reap these benefits, enterprises need to leverage their most strategic asset – their data. The right data volume and quality are critical for the success of AI applications. Respondents recognize 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 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 mostly 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. Enterprises need support on data management and migration. While AI is seen as a shiny new tool that will revolutionize 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 organizations combine vision, strategy, technology, and skills. Now is the time to step back, take stock, build a true Industrial AI plan and turn the hype into reality.”