Organisations face multi-layered vendor hype. To prevent unmaterialised gains, leaders must counter biased research and narrative capture using scientific validation and lifecycle economic modelling.
Effective AI coding governance requires automated, pipeline-integrated architectural controls and risk-proportional human review, not just unenforceable, paper-based acceptable use policies.
AI-assisted development requires explicit review criteria, targeting common machine flaws in correctness, security, and quality, reinforced by team-shared failure logging.
Great insights into medical industry and the use of AI scribe. There are key considerations that my organisation needs to consider when a) integrating AI capabilities into our environment and b) becoming more acquainted with the medical industry, more so health tech – as this has not been a primary area of service for us in the past. Thank you. Digital Engagement Partner, Not For Profit
In April, rising ICT costs and AI complexity drive a shift toward data-led licensing, risk-based funding, and federated governance to ensure value.
Microsoft pivots from AI hype to workflow integration via its three-layer platform, yet adoption faces hurdles regarding governance and cost.
How do you anticipate these shifts in AI pricing models will impact your organisation’s long – term software budget and vendor strategy?
IBRS provided what I would call a foundational document in terms of seeing CEnet’s history. That study that was done back in 2011 really did inform the one strategy. And we still refer to it today. The relationship that we have with IBRS. It’s been long, but it’s been probably the most important from a consulting research perspective that CEnet has had over its lifespan.
NetSuite’s Sydney announcements confirm that embedded agentic AI is becoming standard ERP kit, shifting the focus from custom builds to governance and workforce adaptation.