Top Concern for Enterprise CIOs in 2025: The Urgency of AI Adoption

Ask any commercial CIO what concerns are top of mind as we approach the end of this year and prepare for the next, and you’re likely to hear one resounding answer: artificial intelligence (AI).  No longer just a buzzword, AI is a pivotal element reshaping the strategic priorities of businesses and CIOs across industries. Organizations attributing at least 20% of their profitability to AI use it to create new products, optimize development and expand revenue streams.

The value of AI lies in the competitive advantages it promises to those who harness it — including increased efficiencies, growth in innovation and the potential for new revenue streams across the commercial enterprise.

CIOs find themselves at the forefront of the AI transformative wave. Seventy three percent of US companies have already adopted AI in one form or another, according to PwC. It’s not a question of “if” your organization will adopt AI, but how effectively you can integrate AI into your operations and business strategy to realize tangible returns. Is the investment justified by the potential growth and efficiency gains? This is the question CIOs must answer.

To set the right foundation for AI value, there are two factors CIOs must prioritize: data stewardship and AI security.

Data fuels smarter decisions. By analyzing past trends, predicting future outcomes and understanding the impact of business performance, data and insights help organizations navigate uncertainty and identify opportunities. But AI has put a new pressure and lens on data.

Data hygiene and governance has always been a staple IT process, but it wasn’t a priority for most organizations. The focus for many has been capturing and recording data. Now, the quality of your data is critical; you can’t successfully implement AI without it. The quality of data directly influences not just AI outcomes, but business outcomes. Poor data can lead to AI "hallucinations," inaccurate predictions and potentially harmful decisions.

1. Data integration: How do you get all your data in one place so you can run a query on it? Consolidating diverse data sources into a single, accessible repository is essential for running comprehensive analyses and turning data into AI insights.
   
   
2. Data quality: Outdated or erroneous data can skew AI outputs. Data cleansing, deduplicating and integrating are essential for good data quality. You need good data to leverage AI effectively.
   
   
3. Data ethics: Adhering to legal and ethical standards in data sharing is crucial. The rise of publicly available AI tools has heightened concerns about data misuse and liability. Just because you can share data doesn’t mean you should.

Failure in these areas can result in unintended consequences, from propagating misinformation to discriminatory bias. If your data is bad, your AI outputs could result in proliferating “fake news” or misguided business decisions.

Speaking of liability, this wave in AI innovation brings with it unique security challenges as well. At its most simple, the challenge is twofold: How do you secure AI? And how do you leverage AI to make your security better?

As organizations increasingly rely on AI to accelerate their business strategies, they inherently create more opportunities for security breaches. The safe use and safeguarding of these tools and their data adds a new layer of complexity to security strategies. Diligent identity and access management (IAM) will be critical in reducing potential for unethical, unintended and unauthorized exposure as access to AI tools proliferate.

When it comes to improving your security strategy, the relationship between security and AI might be seen as almost symbiotic as the focus continues to shift from a zero trust to an antifragile philosophy. Antifragile implies security that not only withstands stress but actually improves when faced with challenges.

In the context of AI, this means creating security mechanisms that learn and evolve from attacks, becoming stronger and more resilient as a result. For instance, AI can help detect unusual access patterns in IAM, automatically adjusting permissions or alerting security teams. This synergy helps build a robust defense that not only protects against current threats but also adapts to emerging ones.

1. Define the business case: What is the value of AI in reality? The answer to that question is still fuzzy for many organizations, and it will be different for everyone. At this point, the technology has more momentum than the business case. But failing to define the business value before adopting AI puts the cart before the horse.

Serious evaluation of what the business has to gain from these investments is the difference between advancing or dooming business outcomes. And defining that business case means taking a business-first, technology-second approach.

2. Get guidance from experts: Acquiring and retaining the experience and expertise needed to harness the advantages of AI isn’t easy. A recent report indicates that only 12% of IT professionals have the AI skills their organizations require.

The world of AI is still new and it’s innovating very quickly. Collaborating with experienced talent who understands the rapidly evolving AI landscape is non-negotiable for AI success. Partnering with technology experts like CDW can help ensure that success by helping you assess your organization’s AI readiness, mitigate evolving risks and optimize investments.

3. Data governance: Data readiness is essential for the successful deployment of AI in an enterprise. It not only improves the performance and accuracy of AI models but also addresses ethical considerations, regulatory requirements and operational efficiency, contributing to the overall success and acceptance of AI applications in business settings.

Technology experts like CDW can help you assess your AI readiness and help you establish robust data governance frameworks that prioritize data hygiene to optimize your AI outputs.

Striking the intricate balance between harnessing AI’s potential, bolstering security and realizing ROI is the challenge CIOs must address. The rapid evolution of AI underscores the necessity to partner with proven technology experts. A trusted partner can help you assess your organization’s AI readiness, establish good data stewardship strategies, and implement robust AI strategies to ensure the technology enhances, rather than harms, your business operations.