The CIO Professional Network recently brought technology leaders together for a Roundtable focused on what is making its way onto their 2027 agendas.
The conversation started with a question about where attendees would invest an additional 10% of their technology budgets. AI and automation drew the most support, followed by cybersecurity, data and analytics, technology platforms, and talent development.
From there, participants discussed what increased investment in AI looks like in practice, including where the money is going, what organizations expect in return and how those investments affect existing teams and technology.
Why It Matters: AI may be taking up more room in technology budgets, but organizations still have existing systems to maintain, data to prepare and employees to develop. Planning requires leaders to understand what AI is delivering, where it can provide value and whether the organization is prepared to use it effectively. The discussion also showed how decisions about AI spending connect with infrastructure, cybersecurity, data management and workforce planning.
- Bring AI Use Into the Open: Participants described AI use expanding as more employees experiment with available tools. Some organizations are responding with governance councils and centers of enablement to give that activity more structure. Others are looking at network traffic to understand how employees are already using AI and identify uses that could become approved projects. Greater visibility can help organizations distinguish experimentation from applications worth supporting more formally.
- Know What You Expect AI to Produce: Attendees discussed measuring AI according to the work it supports. In one AI-assisted audit process, throughput increased by 600%, allowing the team to complete six times as much work for the same cost. The group also questioned what happens with the time those efficiencies create. Saving employees hours does not automatically create a financial benefit if that time is absorbed by other work without a measurable result.
- Do Not Let Existing Technology Get Lost in the Budget: With AI competing for more technology spending, participants noted that infrastructure upgrades can become easier to postpone. An aging system may continue working well enough to delay an upgrade for another year, but the underlying need remains. Repeated delays can leave organizations maintaining unsupported technology while the eventual replacement becomes more difficult.
- Get the Data Ready: Participants identified data quality, availability and ownership as continuing barriers to additional AI use. Existing technology can leave information distributed across systems or in formats that are difficult to use consistently. Attendees discussed work underway to connect that information, improve its quality and establish clearer ownership so additional AI projects have reliable data to work with.
- Find Out Whether Recovery Plans Actually Work: The group emphasized that redundancy and disaster recovery still require investment even as newer technologies receive more attention. One organization used an AI-based attack simulation to test its resilience and uncovered issues the team had not expected, leading to plans for quarterly simulations in 2027. Participants made a similar point about backups: having one provides limited protection if the organization has not verified that it can restore it when needed.
- Rethink Hiring and Skills Together: Attendees discussed how AI is changing decisions about hiring and team capacity. Agentic coding has allowed some development teams to make up for lost capacity, meaning a departure does not automatically require a replacement. Participants also discussed using open positions to reconsider the skills a team needs, pairing experienced employees with colleagues who are more comfortable with AI and investing in AI literacy across the workforce.
- Keep Business Knowledge in the Conversation: Participants raised concerns about losing years of institutional knowledge when experienced employees leave without documenting what they know. The group discussed using AI to help analyze business rules, systems and other information while keeping subject matter experts involved in evaluating the results. Attendees emphasized starting with the business outcome the organization wants to achieve, then determining where AI can support that work as the underlying technology continues to change.
Go Deeper -> 2027 Starts Now: What’s On Your Agenda? (VIDEO) – CION Member Roundtable
