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The end of “buy before build”?
For twenty years, the default answer to a business problem was often: find the software. AI is changing that equation. Building software is becoming dramatically cheaper and faster, while non-engineers can increasingly create tools around the exact workflows their organisations need. One survey found 78% of companies plan to build more internal tools, while 35% have already replaced at least one SaaS application.
That does not mean Salesforce, Microsoft, or ServiceNow will disappear. It means the moat around packaged software gets thinner. Increasingly, companies can buy the infrastructure and build the application layer themselves. The strategic shift is from software as something you buy to software as something your organisation continuously creates.
The Unseen Revolution: Why 78% of Companies Are Ditching SaaS to Build Their Own Tools
The leadership question
Which software are you currently renting because building it used to be too difficult? And what happens to your competitive advantage when your people can build exactly what they need?
Revisit your technology stack through a new lens: buy the commodity, build the differentiator. But don’t confuse cheap creation with cheap ownership. Governance, security, integration, and maintenance still matter.
In the AI Era, systems thinking becomes the most scarce skill.
A new “workplace paradox” begins to emerge: Everyone on your team is using AI to massively boost efficiency, but the company’s overall decisions are becoming increasingly foolish.
https://www.kucoin.com/news/flash/in-ai-era-system-thinking-becomes-the-most-scarce-skill
The Cost of ‘Good Enough’ Data: Close Enough Is No Longer Good Enough
Most organisations don’t have bad data. They have something almost as dangerous. They have data that is “good enough.”
Is data AI’s next big bottleneck?
A unified data layer that can make data available wherever compute is running, without forcing you to create and manage copies across every location. That gives you the experience of local data at the edge, while maintaining consistency and control across the grid.
https://www.nscale.com/blog/is-data-ais-next-big-bottleneck
Architecting memory and storage in the AI era
With AI inference now driving enterprise workloads, organizations must rethink infrastructure for speed, efficiency, scalability, and performance per watt to unlock AI’s real-world potential.
https://www.technologyreview.com/2026/09/04/1140872/architecting-memory-and-storage-in-the-ai-era/
How AI and cybersecurity are reshaping ServiceNow
With AI putting the squeeze on SaaS providers, ITSM incumbent ServiceNow is embracing a consumption-based shift and an expansion play centred on cyber.
https://www.cio.com/article/4220431/how-ai-and-cybersecurity-are-reshaping-servicenow.html
The Autonomous Enterprise: Why AI, low-code and hyperautomation are converging
AI, low-code and hyperautomation are coming together to make business processes faster and smarter. This approach connects systems, handles tasks automatically and brings people in when human judgment is needed
Gartner Reveals Top Technology Trends in Government
AI, cybersecurity and service delivery.
The key to AI value is hiding in plain sight: Your operating model
New research shows that organizations undergoing AI transformation succeed not by adopting one “best” operating model, but by making intentional design choices and executing them effectively.
https://www.mckinsey.com/capabilities/people-and-organization/our-insights/the-key-to-ai-value-is-hiding-in-plain-sight-your-operating-model
