What changes minds on GenAI? Adopting it

When it comes to the impact of generative AI on business, adopting is believing, according to PwC’s 27th Annual Global CEO Survey. Respondents whose companies have already started widely using the technology reported considerably more confidence than other CEOs in GenAI’s potential to improve the quality of products and services, build trust with stakeholders and change how the company creates value—even as it spurs major changes in the workforce and the competitive landscape.

For chief technology officers striving to overcome scepticism about GenAI, the finding should be a shot in the arm. So should new PwC research showing a marked value boost across multiple industries and sectors when GenAI is applied to existing operating models. For now, those gains owe largely to increased efficiency and productivity. But by harnessing C-suite enthusiasm, CTOs can build on those gains to deploy the technology for broader goals, including business model reinvention. As CTOs establish the pace and breadth of implementation, they should bear five imperatives in mind:

• Manage the tension between risk and reward. Adopting GenAI may ease scepticism about the technology’s impact, but, according to the CEO Survey, it doesn’t necessarily ease fears about its risks. CTOs should address CEOs’ concerns, as well as those of the technical, legal and other leaders working to mitigate potential threats. Start with adopting a Responsible AI framework that sets clear rules around data ethics, policy, governance, bias, fairness, compliance and monitoring. 
• Integrate GenAI with your existing digital strategy. Generative AI’s outputs have the greatest impact when applied to and used in combination with existing digital tools, tasks, environments, workflows and datasets. If you can align your generative AI strategy with your overall digital approach, the benefits can be enormous. 
• Decentralise experimentation. The incredible diversity of GenAI’s capabilities means that high-value, business-specific applications are likely to be most readily identified by people who are already familiar with the tasks in which those applications would be most useful. Centralised control of generative AI application development, therefore, is likely to overlook specialised use cases that could confer competitive advantage. Consider initiatives like internal hackathons to engage individual workers and departments in experimentation and exploration. 
• Have a plan for managing productivity gains. Companies can basically do three things with the productivity gains enabled by GenAI: (1) reinvest them to boost the quality, volume or speed with which goods and services are produced; (2) keep output constant and reduce labour input to cut costs; or (3) pursue a combination of the two. Knowing the best path forward will require a plan centred around answering a few key questions, such as: What is the relative importance of speed, quality and cost improvements? What time horizon are you solving for? What will you do with employees whose skills have become redundant as a result of new generative AI capabilities? 
• Make sure your people are onboard. Regardless of the productivity path you choose to pursue, considering its impact on your workforce and addressing it from the start will make or break the success of your initiatives. To ensure your organisation is positioned to capitalise on the promise of generative AI, prioritise steps to engage employees in the creation and selection of AI tools, invest in AI education and training, foster a culture that embraces human–AI collaboration and data-driven decision-making, and support employee-led innovation.