Software with AI or pure AI? Debate on product vs feature impacts CIO strategies

The AI product versus feature debate presents CIOs with major strategic implications as the market matures. With artificial intelligence rapidly spreading across the technology landscape, IT leaders face crucial decisions about whether to invest in standalone AI solutions or products with embedded AI capabilities—choices that will significantly impact their organization’s competitive positioning and technology stack for years to come.

The big picture: The AI market is developing along two distinct paths—specialized AI products competing with traditional software platforms that are rapidly integrating AI capabilities.

• On one side are pure-play AI companies offering specialized solutions and foundation model providers like OpenAI, Meta, and Google creating standalone LLMs.
• Meanwhile, established vendors such as Salesforce, ServiceNow, and cybersecurity companies are aggressively adding AI features to enhance their existing products.

Why this matters: How organizations choose to implement AI will determine their technology architecture, vendor relationships, and competitive advantages for years to come.

• CIOs must determine which approach—standalone AI products or software with embedded AI features—will deliver the most value for their specific organizational needs.
• These decisions are particularly challenging when the market’s long-term direction remains unclear and rapid consolidation appears likely.

Market outlook: Many experts predict substantial market consolidation with AI functionality eventually becoming primarily an embedded feature within existing software platforms.

• The AI market is expected to largely merge into the SaaS space over time.
• Software vendors are incorporating AI features specifically to increase customer lock-in effects.
• AI will increasingly be delivered as an add-on feature to existing software packages rather than as standalone products.

The ROI equation: CIOs need rigorous evaluation processes to determine AI value regardless of its implementation model.

• Andreas Welsch, chief AI strategist at Intelligence Briefing, emphasizes the importance of thorough ROI calculations when evaluating AI investments.
• IT leaders must clearly understand what they’re buying and how they’ll extract business value from it.

Between the lines: The dichotomy between product and feature may ultimately be a false choice in the evolving AI landscape.

• Gulce Karsli-Rozenveld, CEO of Oojo, suggests AI will function as both product and feature, comparing it to electricity—simultaneously a utility and a force powering other technologies.
• This dual nature requires IT leaders to maintain flexibility in their approach to AI implementation.

Practical steps: CIOs should follow several key practices to navigate the uncertain AI landscape.

• Conduct thorough due diligence on all AI investments, whether standalone or embedded.
• Maintain flexibility to adapt strategies as the market evolves.
• Evaluate the total bundled value of AI-enhanced software versus best-of-breed AI point solutions.
• Balance innovation potential against integration requirements and security considerations.
• Demand clear ROI evidence before making significant investments.
• Develop strategies to mitigate vendor lock-in risks.

The bottom line: As Karsli-Rozenveld notes, “No tech is a 100% sure bet 100% of the time,” requiring IT leaders to remain adaptable and ready to pivot if their chosen AI approach fails to deliver expected results.