Shieldbase
May 26, 2024
The Evolving Role of the CIO in the Age of AI
For years, Chief Information Officers (CIOs) have sought greater recognition from senior management, and the advent of generative artificial intelligence (AI) might finally provide the breakthrough they need.
Opportunities for CIOs with AI
Many organizations are grappling with how to navigate their AI journey, presenting a prime opportunity for CIOs to assert their influence. Trevor Schulze, Chief Digital and Information Officer at Alteryx, a company specializing in analytics automation, emphasizes this potential.
A Seat at the Table
"This is the opportunity for CIOs to really have a seat at the table. We’ve been talking about a seat at the table for years," Schulze stated at a recent roundtable event in London. This sentiment highlights the critical juncture at which many CIOs find themselves—poised to lead their organizations through the complex terrain of AI implementation.
The Strategic Importance of AI Ownership
Schulze notes a trend where more CIOs are being placed in positions to guide AI strategy, with boards increasingly seeking someone other than the CEO to fill this role.
CIOs as AI Strategy Leaders
"AI strategy should be owned by the CIO," he argues, citing their comprehensive understanding of technology, potential risks, and business processes. This knowledge positions them uniquely to integrate AI into the organization effectively. CIOs are in a prime position to drive AI initiatives, given their expertise in both technology and business operations. Their ability to connect the dots between different departments and technological capabilities makes them indispensable in formulating and executing AI strategies.
Three Paths to AI Integration
Schulze identifies three primary ways AI is currently being integrated into businesses.
Building Proprietary AI Projects
Firstly, companies are developing their own AI projects. Many CIOs are engaging in proof of concepts and pilot projects, with a focus on responsible AI.
"Most everyone has moved at least one business process into being AI-enabled," Schulze observes. As we progress through 2024, he anticipates more production-grade AI capabilities, especially generative AI, becoming mainstream. This shift signifies a growing maturity in AI adoption, where initial experimentation transitions into operational implementations that deliver tangible business value.
Recent research by Alteryx with European tech decision-makers reveals that, since early 2023, organizations have run an average of three AI pilot projects. An impressive 74% of these pilots have been successful, with 53% finding it easier than expected to achieve results. Early adopters are experiencing unusually swift returns on investment, capturing boardroom attention.
Embedding AI in Existing Software
The second avenue for AI integration is through suppliers embedding AI capabilities into existing software and services. This requires CIOs to evaluate and decide on the deployment of these features.
"Every single vendor out there has an AI solution that a CIO has to assess," Schulze points out. The proliferation of AI capabilities embedded in enterprise software means that CIOs must continuously stay informed about the latest advancements and determine how these new features can be leveraged to enhance business processes and outcomes.
The Rise of Shadow AI
The third method is the rise of shadow AI, where individuals within the enterprise procure AI services without the tech organization’s knowledge. This can lead to significant challenges regarding corporate data privacy and security, necessitating CIO oversight. Shadow AI introduces risks that can undermine the organization’s overall AI strategy, including data breaches and inconsistent application of AI technologies.
Pragmatic and Proactive AI Adoption
CIOs must adopt a pragmatic yet proactive approach to AI, focusing on identifying productivity enhancements and strategic opportunities. Schulze asserts, "Every industry will find transformative business processes driven by AI."
Defining Responsible AI Policies
Many companies begin their AI journey by defining a responsible AI policy, outlining permissible uses of generative AI, where outcomes can be less predictable than traditional IT.
### Navigating Deterministic to Stochastic Technologies
Schulze highlights the shift from deterministic to stochastic technologies, which requires careful consideration of innovation boundaries. This shift challenges traditional IT paradigms, requiring new approaches to managing and mitigating risks associated with AI’s inherent unpredictability.
Initial Focus on Low-Risk Areas
Currently, organizations are targeting lower-risk areas for AI application to observe its impact. Research by Alteryx indicates that the path to leveraging generative AI is complex and fraught with potential issues, such as AI generating infringing content (40%) and unexpected outputs (36%).
Addressing AI Hallucinations and Ethical Concerns
The most significant concern, impacting 62% of respondents, is AI hallucinations—producing incorrect or nonsensical results. Only 33% of leaders ensure their training data is diverse and unbiased, and just 36% have ethical guidelines in place. Data privacy and security policies for generative AI are reported by 52% of respondents.
Overcoming AI Implementation Challenges
Challenges include security concerns (41%), data privacy issues (39%), and the quality and reliability of AI outputs (32%). The lack of AI skills is a persistent problem, with 20% of businesses lacking mandatory AI training and 28% citing a talent deficit as a barrier to scaling AI.
Leveraging Existing Data for AI Innovation
Schulze underscores a critical, often overlooked opportunity: utilizing existing data to fuel AI. "We are swimming in data," he notes, with 80% of industrial data remaining untapped.
"This is an opportunity for data owners to create novel AI capabilities. The focus should shift from general-purpose models to leveraging unique data for organizational advantage."
Turning Data into a Strategic Asset
The untapped potential of vast data reserves presents a strategic advantage for businesses willing to invest in AI. By harnessing this data, organizations can develop customized AI solutions that provide a competitive edge, driving innovation and operational efficiency. Schulze advocates for a paradigm shift where companies move beyond traditional data management practices to actively exploit their data assets for AI-driven insights and capabilities.
Embracing the AI Future
As generative AI continues to evolve, CIOs are uniquely positioned to lead their organizations into this new era. By taking ownership of AI strategies, staying informed about new developments, and addressing the challenges head-on, CIOs can ensure their organizations not only keep pace with technological advancements but also derive significant value from AI innovations. The journey requires a balanced approach—embracing the potential of AI while carefully managing its risks and ethical implications.
