How CIOs Can Navigate a Disrupted Software Market

This audio is auto-generated. Please let us know if you have feedback. The software industry faced upheaval this year amid fears that AI and autonomous agents would replace traditional vendors. Beyond the rapid changes, CIOs will need to think more long-term than initial financial impacts suggest in order to support their organizations through AI adoption efforts, Forrester research released this month found. Advancements in AI will either replace or make current features of software platforms less important, Forrester VP and Principal Analyst Craig Le Clair told CIO Dive. In some cases, frontier models are taking over content generation and synthesis previously done by software platforms, or they’re decreasing the number of licensed SaaS subscriptions an organization needs, the research found. After analyzing more than 200 technology and service markets, Forrester researchers identified nine key factors that can indicate the potential for AI disruption of a given software vertical. The drivers of disruption include commercial models, R&D allocation, asset intensity, switching costs, regulatory friction and AI substitutability, the last of which marks the clearest form of disruption, according to Le Clair. “All of these software platforms have built tons of IP in solving a problem, and if that problem could be solved more easily by AI, then that’s going to be a disruptive element,” said Le Clair, co-author of the report. “Not the only one, but a big one.” Biggest disruptions Amid the reshaping of the software ecosystem, AI deployment is stoking demand for infrastructure, data identity, access and network security markets. But application development and software, technology services and growth and transformation services will be the most disrupted, Forrester found. Developers have already been feeling the effects of widespread AI deployment. The rise in price of tokens will lead AI coding to become more expensive than an average developer’s salary by 2028, according to a June report from Gartner. Many engineering roles have shifted from developing code to managing AI. Keep up with the story. Subscribe to the CIO Dive free daily newsletter Several developer skills are becoming obsolete, such as debugging, unit testing and refactoring, or converting code to a more modern base, Le Clair said. It’s one of the clearest cases of AI substitutability currently playing out, he said. “The whole software development lifecycle is being collapsed,” Le Clair said. “It’s being reduced, and that’s going to disrupt those companies.” Technology services will feel similar effects, as app generation platforms will reduce the number of hours firms will be able to bill, since software can be developed by customers themselves. Much of the consulting work in growth and transformation services will also take a hit as companies will be able to use AI to create strategic roadmaps and document their existing processes. Instead of having to run complex simulations as part of a process redesign, Le Clair said companies are pushing AI models to find bottlenecks and suggest improvements. “Autonomous testing platforms, disrupted collaborative work management tools, content platforms — these are all areas that are, I think, going to need significant infusion and execution to survive,” Le Clair said. What can CIOs do? There are ways in which CIOs can take advantage of the continuous change to impacted technology services, Le Clair said. As vendor costs shift and talent needs evolve within organizations, the most successful tech executives will continually audit their software vendors’ abilities to ensure they match their organization’s current needs. CIOs should work to identify which features from their vendors are becoming commoditized by agentic AI or integrated with newer offerings, Le Clair said. This involves looking at the entire portfolio of an organization’s software tools and assessing if they should continue to invest in a tool, or if one of their AI offerings can handle the same task. The rapid deployment of AI has created cost concerns for enterprises as many IT professionals say they lack visibility into their AI software usage. About three in five IT professionals said AI overspend had increased at their organization, according to a June report from Flexera, with wasted spend on SaaS growing 10 percentage points in the last year. Getting a baseline understanding of abilities will help keep a tech leader from investing in dead-end tools that may soon be neutralized by alternatives, and can help reduce an organization’s technical debt, Le Clair said. “Every vendor briefing paints this really rosy picture of how they’re enhancing their capabilities,” Le Clair said. “That’s just not going to be the case for a lot of them. There’s going to be too much native AI competition for what they’re doing.”