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How CIOs are Evaluating and Harnessing AI in their Growth Agendas

There’s no doubt that the integration of AI into IT operations has emerged as a “game-changer”. It’s rocked industries, spurred debate, and—with a global projected AI spend of $3 trillion between 2023 and 2027 (Gartner)—it’s also at the forefront of CIO priorities. Many CIOs are analyzing, predicting, and voicing opinions on how AI will revolutionize how businesses operate and innovate in the IT space. However, where exactly do CIO priorities lie? And how can industry leaders correctly choose which specific AI tech they should invest in?

The role of AI in addressing key CIO priorities

In 2024, the CIO mandate remains unchanged: steer an organization’s use of AI and other emerging technologies to boost productivity and revenue.

The key is ensuring ROI with strategic decisions regarding foundational cloud systems, data management, and IT operations. Deploying new technologies that enhance operational efficiency and customer service is also important. AI plays a crucial role in addressing a wide range of these priorities:

  • Cloud-first initiatives: AI enables organizations to optimize cloud strategies, providing timely and cost-effective migration.
  • Realizing operational efficiencies: Leveraging AI-powered digital technologies streamlines operations, driving cost savings and enhancing productivity.
  • Expanding operational landscape: AI facilitates the seamless integration of hybrid, remote, and edge environments, making sure businesses remain agile and competitive.
  • Upskilling/reskilling IT staff: AI catalyzes upskilling IT professionals, equipping them with the necessary expertise to navigate the digital landscape effectively.
  • Planning for AI/gen AI: The emergence of AI and its subsequent evolution into Gen AI prompts organizations to strategize and prepare for the future of intelligent technologies.
  • Enhancing technology security: AI-driven security solutions fortify defenses, safeguarding businesses against evolving cyber threats.

Overcoming concerns and hesitations

With the plethora of new AI tech, there are common concerns surrounding AI adoption, including cybersecurity risks, accuracy, government regulation, job displacement, and ethical considerations. According to the 2024 Edelman trust barometer, there remains a gap in trust between consumers and emerging technology. Business leaders are prioritizing managing these valid concerns, especially with the use of AI tech among their teams.

Executives are also responsible for evaluating which technologies to purchase to maintain a competitive edge and lead the curve in performance and innovation. On the flip side, leaders want to be calculated when making large investments and don’t want to run the risk of investing too much in technology yielding little to no ROI.

A framework for evaluation

A key concern of leaders is evaluating which specific technologies to invest in. Consider this preliminary framework:

  • Remaining at the forefront of technological advancements: Embracing early adoption provides a competitive edge, boosts efficiency, and maintains market significance.
  • Exercising caution in early investments: Prioritizing effective risk management, resource allocation, and adaptability is crucial to preventing potential operational disruptions.
  • Strategies to balance innovation and caution: conducting pilot projects, engaging in continuous evaluation, ensuring scalability, mitigating risks, and fostering collaborative partnerships help cultivate well-informed decisions.
  • Conduct thorough research: research thoroughly and understand the potential benefits and risks associated with each technology. This includes evaluating market trends, competitor strategies, and industry best practices.
  • Assess business needs: align technology investments with the specific needs and goals of the organization. Prioritize technologies that address critical business challenges or present opportunities for growth and innovation.
  • Pilot projects: Start with small-scale pilot projects to test the feasibility and effectiveness of new technologies in real-world scenarios. This allows for a practical evaluation of their potential impact before committing to larger investments.
  • Collaborate with industry experts: Seek guidance from industry experts, consultants, or technology partners who have expertise in the relevant field. Their insights and experience can provide valuable perspective on the viability and suitability of different technologies.
  • Establish clear evaluation criteria: Develop clear criteria for evaluating potential technologies, considering factors such as cost, scalability, compatibility with existing systems, and potential return on investment. Use these criteria to objectively assess and compare different options.
  • Risk management: Implement robust risk management strategies to mitigate potential downsides associated with technology investments. This may include contingency planning, setting aside reserves for unforeseen challenges, and establishing clear escalation protocols for addressing issues as they arise.
  • Embrace agility: Recognize that technology landscapes are constantly evolving, and it’s essential to remain agile and adaptable. Be prepared to pivot or adjust investment strategies in response to changing market conditions, emerging trends, or new opportunities.
  • Seek feedback and iteration: Encourage open communication and feedback loops within the organization to continuously evaluate and refine technology investment decisions. Solicit input from stakeholders across different departments and levels to ensure alignment with broader business objectives.

AI business leaders have considered this risk measurement framework and now deliver curated services to aid existing and potential customers with several of the strategies above. For example, many companies provide capabilities within their technologies to measure ROI, allow for constant feedback loops, or begin with smaller projects to prove value before scaling. Ultimately, there’s a cross-industry understanding that with “the next big thing” comes uncertainty, questions, and a rush to manage investments properly.

However, if navigated correctly, the integration of AI into IT ops heralds a new era of efficiency, productivity, and innovation. By embracing these new tools and adopting a strategic approach to investment and implementation, businesses can unlock unprecedented opportunities for growth and success in the digital age.


The FORRESTER WAVE™: End-User Experience Management, Q3 2022

The FORRESTER WAVE™: End-User Experience Management, Q3 2022