Published on January 16, 2024, 6:55 am
Ensuring the success of generative AI strategies requires productive partnerships between organizational end-users and increasingly intelligent software tools. However, this collaboration often faces challenges that require coaching and coaxing. CIOs are finding themselves in the difficult position of preparing their organization’s end-users to co-exist with generative AI.
While many experts argue that generative AI tools like large language models (LLMs) and Microsoft Copilot assist rather than replace workers, the rapid influx of generative AI products and the implementation of LLMs in various tasks have complicated this argument. The relationship between artificially intelligent machines and human workers is becoming complex.
The stakes are high, as Reuven Cohen, strategic AI advisor to Fortune 500 company Baxter International, points out. Organizations must decide whether to augment or replace their workforce with AI. Empowering the most capable individuals within the organization with tailored AI is the first step, but determining who is “less capable” will depend on technology’s evolution and the progress of human-machine partnerships.
Currently, most CIOs are deploying generative AI to enhance productivity and efficiency. According to Gartner, 77% of CIOs are using generative AI for this purpose. The United States Patent and Trademark Office (USPTO), for example, sees AI as an augmented intelligent tool that helps examiners focus on more analytical work instead of clerical tasks.
CIOs need to discover how human workers can effectively utilize LLMs to add value to their work. Mike Mason, Chief AI Officer at Thoughtworks, emphasizes that CIOs should consider the impact of AI on their workforce and ensure proper management, training, and integration for maximum return on investment.
Despite calls for caution by industry leaders about AI’s potential risks, major corporations like Goldman Sachs, Fidelity Investments, Procter & Gamble, American Express, Gilead Sciences, among others have publicly developed and deployed LLMs to boost productivity and innovation. However, CIOs must develop upskilling and governance strategies to ensure employees can benefit from new generative AI implementations.
Evolutions in generative AI technology and interfaces will transform how workers utilize these tools. Accenture claims that generative AI tools are becoming more “human by design” with refined conversational interfaces, robots that respond to voice commands, and software that augments natural human work processes.
Conversational AI is gaining importance in the enterprise as it provides substantial answers to questions over time. Other valuable use cases for industries include content generation, document summarization, analysis, insight extraction, and decision-making algorithms that require human augmentation.
However, it remains unclear how workers can add value to these tools designed to learn as they go. Human creativity will be necessary to elevate the quality of applications. Gartner advises CIOs to establish guiding principles for human-machine interactions. A combination of careful consideration of stakeholder workflows and implementing data readiness and security measures are prerequisites for successful implementation.
Generative AI requires human oversight, experience, accuracy assurance, quality outcome management, and safety protocols. CIOs must prioritize education and training sessions while gradually implementing generative AI tools into the workplace. Workers should be reassured that AI is meant to augment their work rather than replace them.
Some organizations are taking additional steps beyond training programs to address workers’ concerns about the impact of AI on their roles. Microsoft partnered with AFL-CIO to keep dialogue open regarding AI development’s impact on workers’ needs and roles while actively incorporating worker feedback into shaping supportive policies.
The rapid pace of innovation in generative AI platforms is exciting for developers and eagerly anticipated by enterprise executives. However, the cost of building and deploying generative AI solutions may restrain enterprise adoption.
As CTOs evaluate new technologies for their companies, evaluating factors such as cost versus return on investment becomes crucial. Ultimately, strategizing for a workforce that integrates generative AI tools is essential for CIOs and CTOs.