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Since the release of ChatGPT by OpenAI in November 2022 – with its ability to create compelling, relevant content, new large language model (LLM) technology – business leaders, especially CEOs, are being pressured to accelerate new generative AI investments. IBM IBV surveyed executives to assess their progress and concerns and their adoption strategies.

Adoption of generative AI is still in its very early stages. Most organizations are only beginning to figure out how and where to make use of it. In fact, as few as 6 percent of executives in new surveying conducted by the IBM Institute for Business Value say they are operating generative AI in their enterprise today.

In contrast to many peoples’ expectations about AI, automating tasks is not the top priority for executives looking to tap generative AI to grow business value. Looking at benefits by function, research and innovation is the primary area where organizations see opportunities for generative AI.

IBM IBV's recent survey of executives found that the key barriers to the effective deployment and use of generative AI are linked to security, privacy, ethics, regulations and economics – not access to the underlying technology itself.

Organizations will have to evaluate where in their enterprise the potential gains and cost efficiencies outweigh the risks of possible errors or unintended consequences from the use of generative AI along with broader ethical considerations. Ecosystems expand generative AI opportunities to harness data, insights and technology capabilities from across partners and stakeholders while enabling control over the capabilities that are most central to an organization’s value proposition.

The authors show how cognitive computing offers companies an opportunity to dramatically improve the efficiency of business functions throughout the enterprise – from core back office systems to critical middle office capabilities to essential front office functions.

Examples are given of companies that are using cognitive computing to transform the workings of individual business functions.

Cognitive systems will also create breakthrough opportunities for interactions between various functions of the organization.

Self–learning cognitive systems are enabling better-informed customer engagement in which the technology recognizes, learns and improves with every interaction.

Applied to innovation activities, cognitive computing helps organizations better formulate hypotheses, identify and validate new ideas, accelerate and refine scenario envisioning and planning. As organizations become more mature in both digital intelligence and digital re-invention, the dynamic interplay between functions will increasingly become a source of competitive advantage.

The authors address how a combination of artificial intelligence (AI) and cognitive computing --- adaptive data management systems that monitor, analyze, make decisions and learn -- will transform businesses, work and customer offerings.

A survey of 6,050 C-suite executives worldwide identified a small group of cognitive innovators and revealed what they are doing differently.

Cognitive innovators identify customer satisfaction, retention, acquisition and revenue growth as the primary rationale for embracing cognitive technologies.

Cognitive computing systems are already helping make sense of the deluge of data spawned by ordinary commerce because they are able to adapt and learn.

The authors offer a four-step approach to cognitive computing innovation based on their research findings.

Most recent C-suite surveying suggests current applications of generative AI, although hyped, are fragmented and unlikely to yield major financial returns anticipated. Instead, business leaders expect major value from generative AI will be achieved through application of generative AI to innovation: operational innovation, product and service innovation, and most elusive of all, business model innovation.

Findings and analysis presented draws on data from several surveys of C-level executives conducted by IBM Institute for Business Value in collaboration with Oxford Economics during 2023. Each survey focused on the potential of generative AI in a particular business area. The n-count of each survey ranged from 100-3000.

1. Business leaders expect generative AI to build on returns achieved from investments in traditional AI, with 10 percent RoI expected on generative AI investments by 2025. 2. Executives anticipate that generative AI will have most impact when implemented to expand innovation. 3. Specific examples provided for operational innovation, product innovation, and business model innovation

We are still very early in the generative AI development cycle. We have made best efforts to project, but only time will tell for sure.

Business application of generative AI are extremely fragmented. Despite the desire to throw investments at the wall to see what sticks, it is important that leaders take a structured approach to generative AI, focusing on RoI from innovation investments.

To alleviate negative impacts of generative AI, focusing on innovation potential and value maximization is crucial.

This research is based on completely new surveying and data. This papers adds to the sum total of new knowledge in the generative AI domain.