CEOs around the world are placing a strong emphasis on productivity, according to a recent study by the IBM Institute for Business Value. The study found that nearly half of the CEOs surveyed (48%) identified productivity as their organization’s highest business priority, closely followed by tech modernization (45%). This shift underscores the growing understanding among CEOs that embracing technological advancements is crucial for achieving their productivity objectives.
CEOs are becoming more cognizant of the impact of generative AI on competitiveness, as indicated by the study. For four years in a row, CEOs have identified technology factors as the primary external force shaping their organizations in the coming years. A remarkable 75% of the surveyed CEOs recognize that being at the forefront of generative AI advancement can deliver a substantial competitive edge.
Furthermore, generative AI is already driving notable changes in the workforce. CEOs report that 43% have implemented workforce reductions or redeployments due to the adoption of this technology. On the other hand, 46% have hired additional employees as a direct result of generative AI, with plans for further recruitment in the future.
Despite these workforce shifts, the study reveals a lack of comprehensive assessments regarding the impact of generative AI. Merely 28% of CEOs have evaluated the potential effects on their workforce, while 36% plan to do so within the next 12 months. This emphasizes the need for CEOs to proactively understand and manage the implications of generative AI on their employees.
In terms of decision-making, CEOs increasingly rely on operational, technology, and data leaders. COOs (62%) and CFOs (52%) are identified by CEOs as the key C-Suite members who will play crucial roles in strategic decision-making.
Notably, the influence of technology leaders is growing, with a significant increase in CEOs pointing to CIOs (38%) and Chief Technology/Chief Digital Officers (30%) as important decision-makers, highlighting the expanding role of technology expertise in the decision-making process.
Challenges faced by CEOs in generative AI adoption
- There appears to be a disconnect between CEOs and their executive teams when it comes to AI readiness. While 50% of CEOs report integrating generative AI into their products and services, and 43% use it to inform strategic decisions, only 29% of their executive teams feel they have the necessary in-house expertise to adopt generative AI. Similarly, only a mere 30% of non-CEO senior executives believe their organizations are ready to responsibly adopt generative AI.
- While executives acknowledge the benefits, they also express apprehension about potential risks and barriers associated with the technology, including concerns about bias, ethics, and data security. 57% of CEOs surveyed worry about data security, while 48% are concerned about bias or data accuracy.
- Two out of three CEOs are navigating the AI landscape without a clear plan to assist their workforce during inevitable transitions and disruptions caused by AI.
- The absence of clarity surrounding AI’s impact is hindering CEOs’ ability to make informed decisions and investments.
- 56% of CEOs are deferring major investments due to the absence of consistent standards. This lack of standardization affects various areas, including emerging fields like sustainability, data, and privacy.
How can CEOs enhance decision-making in the age of AI?
Unlocking the full potential of generative AI and driving productivity requires CEOs to take decisive action. Here are essential steps CEOs must follow to make timely decisions and seamlessly integrate generative AI into their organizations, propelling them towards success.
- Technology and data literacy: Provide targeted training to ensure everyone in the organization is well-versed in technology and data, with a focus on AI. Elevate individuals, such as the Chief Data Officer (CDO), who possess expertise in aligning business strategy, technology strategy, and data strategy.
- Outcome-oriented approach: Emphasize “outcomes over activity” as a guiding principle. Be ready to terminate projects that do not deliver intended value, support strategic goals, or adhere to ethical guidelines.
- Effective data utilization: Utilize various planning approaches, including forecasting, modeling, scenario-based planning, benchmarking, and data mining. Leverage the expertise of the CDO to make informed decisions about data and cybersecurity, encompassing areas like data management, reliability, regulatory compliance, ownership, and integration.
- Balanced sustainability and profitability: Engage the Chief Sustainability Officer (CSO) and Chief Financial Officer (CFO) to develop a roadmap that aligns sustainability goals with profitability objectives.
- Workforce impact assessment: Evaluate the potential impact of generative AI on the workforce. Proactively plan to support employees through disruptions and facilitate necessary transitions.
- Digital-first solutions: Implement digital-first solutions to enhance efficiency, engage talent, and foster the development of new skills. Encourage collaboration between individuals with diverse skill sets to co-develop AI and redesign workflows.
- Talent acquisition and alignment: Recognize potential skills shortages and align top talent with areas crucial for maintaining competitive advantage.
- Principles-based AI use cases: Identify AI use cases that align with the organization’s principles, technical guidelines, and architecture. Prioritize applications where AI can drive competitiveness, innovation, and unique business value.
- Robust security measures: Accelerate the transition to zero-trust security across the enterprise and partner network to ensure secure interactions, workflows, and innovation. Establish consistent standards and governance, particularly in the realms of generative AI and quantum computing.
- Resilient enterprise: Simplify processes, digitize operations, and establish strategic partnerships to build a resilient enterprise. Embrace open innovation and leverage external and open data to create new opportunities. Develop a common platform using open hybrid technology that is scalable, consistent, and optimized for both the organization and its partner ecosystem.
Read the full report here.
Source credits: IBM study – CEO decision-making in the age of AI, Act with intention
