Navigating the Generative AI Revolution: Challenges and Strategies for CIOs

In today's rapidly changing IT landscape, Chief Information Officers find themselves at the forefront of a transformative IT revolution driven by generative AI. We all hear about the transformation this technology is driving in the media every day - but it also poses significant challenges for organizations.

The November 2022 launch of ChatGPT set the stage for a surge of interest and investment, with a Gartner report from May 2023 revealing that 45% of executives were prompted to increase their AI investments in response to ChatGPT's publicity.

The adoption curve for generative AI is steep, with 70% of organizations actively exploring its potential and 19% already in pilot or production mode, according to the same report. To effectively leverage the benefits of generative AI for the enterprise, CIOs and CDOs must address a variety of issues when crafting their AI strategies.

Generative AI is a disruptive technology. CIOs and their C-suite peers must consider how their company will be impacted by this force. Some companies have already lost significant market value as they faced sudden competition from generative AI. CIOs must balance expectations of cost savings with the need to strengthen their offerings by incorporating this technology.

Despite ongoing economic headwinds, only 17% of executives indicated cost optimization as the primary purpose of generative AI investments. Customer experience [see also here] was the most common primary focus of investments, cited by 38% of 2,500 executives polled for the afore mentioned Gartner report.

Strategies for Successful Implementation:

Building an Engine in Flight: As if those aren't big enough challenges to tackle, executives must move fast and tackle them while everything is in flight. CIOs should apply agile processes to their gen AI strategy. Learning as things progress, doing safe and controlled iterations, and focusing on risk management is essential in this rapidly evolving landscape.

Enterprise Technology Architecture: Organizations will use many generative AI models of varying size, complexity, and capability. To generate value, these models need to work together and with existing systems or applications. Building a separate tech stack for generative AI creates more complexities than it solves. CIOs must ensure that generative AI models integrate seamlessly with the existing technology stack.

Navigating the Uncertain Terrain:

Predicting the future is always challenging - particularly during uncertain times. We all aspire to see improvements in our sales and reductions in our costs, but what actions can we, as leaders, take to ensure that we are prepared for unforeseen events?

What would Henry Ford have done? While many credit Ford as the inventor of the automobile, his true innovation lay in the assembly line, which ultimately transformed every manufacturing industry. If Henry Ford were around today, he would explore the capabilities of this new technology according to his guiding principle: Automate What You Can!

Lack of Guidance: Generative AI is a rapidly evolving field, and there is limited pre-existing guidance and support. Risk guidelines for gen AI are fragile and new. CIOs must navigate this uncertain terrain while ensuring responsible and secure use of generative AI.?

Innovating at Speed: CIOs must identify areas where generative AI can effectively differentiate their organizations and align it with business strategy. The speed of generative AI's evolution and its power and complexity present new challenges for CIOs to ideate, educate, and execute in a different way, in terms of velocity and viscosity of the solutions.

Making Informed Choices

Identifying and Prioritizing Use Cases: Research firm IDC found that nearly 70% of enterprise intelligence services buyers are considering or actively working on use cases for generative AI. CIOs should leverage their past experiences in prioritizing tech-driven initiatives and apply the same rigor to gen AI concepts to ensure wise investments by their organizations.According to IDC's survey, the most critical use cases are within the realms of knowledge management, code generation, and product or service design and engineering. Survey respondents most strongly concurred with the idea that generative AI will empower their employees to concentrate on higher-value tasks. Foundry Digital Business research's survey on gen AI discovered that retail CIOs are at the forefront in identifying use cases (49%), followed by IT leaders in the manufacturing (42%), technology (42%), and financial services (32%) sectors. Companies need a way to collect, vet, and prioritize ideas on how to use the technology for the benefit of the enterprise. A clear roadmap for implementing generative AI, aligned with the C-suite, is essential.

Buy, Modify, or Build: CIOs must decide how to bring generative AI into their organizations: through acquisition, customization, or building their own models. McKinsey's framework describes three different approaches, with each one having its own considerations in terms of cost, complexity, and control:

• Taker: This approach involves using pre-built capabilities without customization. It's like taking a ready-made solution off the shelf, such as GitHub Copilot for code generation or Adobe Firefly for image editing. Takers rely on publicly available models and are quick to implement.
• Shaper: Shapers integrate generative AI models with internal data and systems to create customized results. For instance, it could support sales deals by connecting AI tools to customer relationship management (CRM) and financial systems. Shaping is ideal for companies looking to scale generative AI, develop proprietary capabilities, or meet specific security or compliance requirements.
• Maker: The least common approach involves building a foundation model for a specific business case. This is a costly and complex endeavor, requiring substantial resources and expertise. Building a model like this can cost tens or even hundreds of millions of dollars due to factors like data volume, model architecture, and compute power.

Ensuring Readiness and Security

Regardless of the approach chosen, a modern technology stack and data program are essential to effectively implement generative AI. CIOs must ensure that the organization's infrastructure is ready to support generative AI capabilities.

Data privacy and security are paramount concerns when using generative AI. CIOs must develop governance policies and controls to prevent proprietary data exposure and ensure compliance with data privacy laws. Monitoring and ensuring data privacy and protection are essential when using generative AI.

Addressing the Human Factor

In a March 2023 report, Goldman Sachs estimated that approximately two-thirds of existing jobs face some level of exposure to AI automation, and generative AI has the potential to replace as much as one-fourth of the current workforce, this implies that up to 300 million full-time jobs could be at risk of automation.

This situation has generated considerable uncertainty among individuals who wonder about the impact on their careers and whether they need to acquire new skills. The executive team should engage with employees to address their concerns and communicate the potential for AI to create new jobs and opportunities.

Upskilling is King: AI is reshaping the demand for IT skills and talent. Workers across the organization will need to learn how to work with generative AI tools. IT workers must retrain to work with generative AI tools and acquire the skills required to support the technology as it's used throughout the organization - also to be and remain a sought-after member of staff in the following years

Leading Through Change

CIOs will be among the executives responsible for leading their organizations through all the disruption that gen AI is expected to bring. They have been building their skills in this space for the past decade as they led their organizations through digital transformations. However, leading through the upcoming change will be different than prior change management scenarios, as the pace of adoption and the disruption gen AI brings could dwarf previous technology revolutions.

The CIO cannot handle these challenges in isolation, nor should they attempt to do so. Collaboration across various teams will be crucial for the successful integration of generative AI capabilities. However, given their pivotal role as the primary technologist in numerous organizations, the CIO is expected to serve as a crucial advisor to the executive team, offering insights into the risks and opportunities associated with generative AI.

The CIO's role extends beyond enabling and equipping; they function as facilitators, advisors, and delivery experts. Consequently, the CIO's role within the C-suite is now integral, as they assist others in comprehending the comprehensive array of tasks that must be addressed.

A quick wrap-up

The transformative potential of generative AI is undeniable, offering faster software development, reduced technical debt, and innovative solutions. However, CIOs must also grapple with the complexities of integrating generative AI into existing technology stacks, ensuring data privacy and security, and addressing employee concerns about job displacement.As organizations navigate these challenges, CIOs are well-positioned to lead the way, drawing on their expertise in technology and change management.

The successful adoption of generative AI hinges on the ability of CIOs to adapt, innovate, and collaborate across teams, ultimately shaping strategies that harness the full potential of this transformative technology. While the path ahead is marked by uncertainty and complexity, CIOs have the opportunity to guide their organizations through the generative AI revolution, driving innovation, efficiency, and competitiveness in the ever-evolving business landscape.?

#ai #genai #generativeai #cio #cdo #strategy #aistrategy

Sources:

• Gartner Inc. 05/23, Gartner Poll Finds 45% of Executives Say ChatGPT Has Prompted an Increase in AI Investment
• McKinsey, 07/23, Technology’s generational moment with generative AI: A CIO and CTO guide
• GoldmanSachs, Joseph Briggs, Devesh Kodnani, 03/23, The Potentially Large Effects of Artificial Intelligence on Economic Growth
• Foundry Digital Business research,Chase McLane, 04/23, Organizations are advancing their digital strategies with AI
• IDC / CIOcom, Mary K. Pratt, 07/23, 20 issues shaping generative AI strategies today
• IDC / CIOcom, Sarah K. White, 06/23, How AI is reshaping demand for IT skills and talent
• Own research