Missing the boat? Why IT Services leaders are struggling in the AI boom.

🌈 Abstract

The article discusses the current state of the AI services industry, highlighting the disconnect between the hype around AI and the reality on the ground for Global Service Integrators (GSIs). It explores why GSIs are missing out on the AI revolution and whether AI will cannibalize existing services more than it creates new ones.

🙋 Q&A

[01] The Valuation Disconnect

1. What is the current performance of GSIs in the AI market?

• GSIs have decoupled from the AI boom, with their stock prices declining by 28% despite $10 billion in announced investments in generative AI.
• As an investment thesis, GSIs have historically delivered consistent outperformance, acting like technology mutual funds run by "insiders".
• However, the concern is that generative AI will automate much of the current work model, pushing more workloads from people to software and eating into future cash flows.

[02] Automation: The line between product and people is changing

1. How is generative AI impacting the Software Development Life Cycle (SDLC)?

• Automation of the SDLC is starting to occur, but not in the way many anticipated. Generative AI is not eating the SDLC from the head (e.g., consulting, analysis, design, and development), but from the tail.
• The "Automation Zone" includes tasks like Quality Assurance (QA), Testing, Application Maintenance, and Application Modernization, which are highly process-oriented and rely on repetitive procedures. Generative AI excels at these tasks, and clients are already demanding 15-40% efficiency gains via AI in this zone.
• The "Confusion Zone" is where predictions of services automation at the front end of the SDLC existed for good reason, as the VC community has poured more than $2 billion into code generation platforms. However, there is no recognizable revenue or margin lift, and clients now have "POC fatigue".

2. What is the current state of enterprise AI adoption at the application layer?

• A generation ago, massive application markets opened up with CRM, HRM, IT Management, ERP, and Supply Chain. Such scale use cases have yet to emerge with AI, and it's not for lack of trying.
• The current wave of AI adoption is inverted from the Cloud wave, as recent as five years ago, where app spending outweighed the supporting infrastructure and semiconductor spend 2:1. But thus far in the generative AI journey, spend on semiconductors (NVIDIA) and infrastructure (Azure, AWS, Google, OpenAI) is outweighing AI application revenue 20:1.

3. What is the author's final thought on the potential for radical changes in the IT services industry?

• The author wonders if any IT services leaders will have the courage to chase Moore's Law to its conclusion and radically change the headcount vs. software model, similar to Elon Musk's actions at Twitter.
• The author notes that winning IT services models have historically correlated highly to what technology wants, and the industry is searching for a new model they can all bet on, 18 months into the generative AI era.