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AI Unleashed: Navigating the Enterprise Potential Amidst Lingering Challenges
LONDON, April 23, 2024 – In a groundbreaking study led by IFS, a leading provider of cloud enterprise software, findings indicate that while business leaders are eager to harness the revolutionary power of artificial intelligence (AI), a disconnect between aspirations and operational capabilities is hindering progress. The study titled "Industrial AI: the new frontier for productivity, innovation and competition" surveyed 1,700 high-level executives and revealed that the issue is not a lack of enthusiasm but a series of barriers including technology, processes, and skills constraints that are keeping AI's promise at bay.
The research unveils a stark contradiction in the world of AI adoption within businesses. A staggering 84% of executives foresee immense benefits from AI, with innovation, data enhancement, and cost-efficiency cited as top value-driving areas. Despite this, there is an overwhelming sense of urgency to embrace AI, with 82% acknowledging the intense pressure to expedite adoption. Even so, concerns are growing among these decision-makers that without proper planning, execution, and communication, AI initiatives are prone to stalling at the pilot stage.
These setbacks stem largely from lack of prioritization and readiness in critical areas of AI development. It has been observed that over one-third of businesses have not taken steps to migrate to the cloud – a step not essential, yet indicative of broader unpreparedness to scale AI endeavors effectively. IFS outlines that a successful industrial AI strategy demands a robust amalgamation of cloud-based infrastructure, data, processes, and skills – assets that 80% of participating executives believe they lack internally in sufficient measure.
Christian Pedersen, Chief Product Officer at IFS, commented on the findings, "AI has the potential to be the most transformational tool the enterprise sector has ever seen. However, our research underscores a prevalent misunderstanding around leveraging AI in an industrial context. It's ironic that AI is expected to drive cost efficiency and margin improvement when the lack of a robust strategy leaves many enterprises under-prepared and under-skilled to meet these goals. To address these challenges, we developed IFS.ai, providing AI across all products and processes, thus enabling customers to achieve tangible benefits faster."
Pedersen further elucidates that achieving transformative impact at scale with AI necessitates clear strategic objectives, recognition of high-impact use cases, and early investment in skills development. This approach promises to reverse the current trend of disillusionment and fulfill the high expectations set by board members and the C-suite.
In terms of AI readiness, a significant skills gap has allowed many companies to fall behind. IFS found that nearly half of the survey respondents (48%) are still in the proposal gathering stage, with a scant 27% having a defined strategy and discernible outcomes. As many as one in five companies are in the infant stages of AI experimentation, and an additional 5% lack any sort of coordinated approach or active AI-related initiatives.
Despite these initial challenges, optimism remains high among survey participants. Nearly half (47%) believe AI could substantially benefit their companies within the next two years, with another quarter (24%) expecting these changes to manifest within a year. Expectations are particularly high for AI's impact on smart production, service delivery, and business and operational management, with other anticipated benefits including product and service innovation, growth-oriented decision-making, talent empowerment, and enhancement of customer experience and service.
To effectively harvest the advantages of AI, companies must capitalize on their most strategic asset: data. The quality and availability of data are critical to the success of AI applications. The respondents recognize the importance of real-time data, with 86% acknowledging its value. However, a mere 23% have completed foundational data architecture capable of driving data-driven decisions and responding to real-time changes – signaling that a considerable effort is still required to make data AI-ready. Additionally, fewer than half (43%) of the companies have broadly structured their data, with some yet unstructured.
Pedersen points out, "The data foundation layer's maturity is essential for a successful AI strategy, without which AI's transformative potential remains an unrealized promise. It's imperative for enterprises to seek support in data management and migration to harness AI's ability to revamp all aspects of business from product innovation to productivity, customer experience, and even ESG commitments. The time is now for a comprehensive assessment and for building a true Industrial AI blueprint to convert the prevalent hype into tangible results."
The study was meticulously carried out by Censuswide, a reputable survey agency, which engaged 1,709 senior professionals across multiple sectors such as Manufacturing, Telecommunications, Services, Construction, and Energy, to name a few. All participating organizations boast annual revenues exceeding $50 million. The demographic includes the UK, USA, Canada, Germany, France, UAE, Norway, Japan, Australia, Sweden, Denmark, and Finland. The survey took place between March 6 and March 27, 2024.
For further information and to access the full details of the research, the following IFS Press Contacts are available:
For the Middle East, Africa, and Asia Pacific regions: Adam Gillbe, Corporate Communications, can be reached via email at [email protected] or by phone at +44 7775 114 856.
For the USA: Mairi Morgan, Corporate Communications, is available at [email protected] and by phone at +44 7918 607 299.
The research findings, graphics, and related documents are accessible for download at the following links:
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The full study report and graphical resources add depth to the discussion and provide a visual representation of the findings. IonicModule
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