After yesterday’s deep dive into AI’s current state, today brought a fascinating shift in perspective – from “if” to “how” in terms of AI’s role in IT operations. The sessions painted a clear picture of both the immediate future and longer-term transformation ahead.
The Foundation of Future Operations Cameron Haight’s keynote brought hard data that cuts through the AI hype. Beyond just the raw investment numbers (54% currently investing, 33% planning to), what really caught my attention was the maturity model he presented. The pathway to AI adoption isn’t linear – it’s a trust-based evolution:
- Human in the loop: Where most organizations start, with AI making suggestions but humans making all decisions
- Human on the loop: Where we’re heading, with AI handling routine tasks under human supervision
- Human out of the loop: The future state, but one that requires earned trust through proven success
A particularly striking statistic: while 41% of CIOs expect I&O work to be augmented by GenAI, only 8% expect full substitution in the next three years. This gap illustrates the realistic view emerging about AI’s role – enhancement rather than replacement.
Event Intelligence Evolution Matt Crossley’s deep dive into Event Intelligence Solutions (EIS) revealed a fascinating progression in how organizations are approaching AI implementation:
Typical Evolution Path:
- Stage 1: Basic correlation and noise reduction (where most start)
- Stage 2: Root cause analysis and triage
- Stage 3: Remediation identification and suggestion
- Stage 4: Automated remediation (where few have reached)
The key insight here wasn’t just the progression, but the prerequisites for success at each stage. Organization maturity in three areas proved critical:
- Data quality and accessibility (cited by 34% as their top challenge)
- Process integration capabilities (29% struggling here)
- People resources and skills (28% reporting this as a major hurdle)
The AI Operations Landscape Today’s sessions revealed a rapidly evolving vendor ecosystem. The landscape includes:
- Established players adding AI capabilities (ServiceNow, BMC, Dynatrace)
- New AI-native vendors emerging (cited as a key trend to watch)
- Open source projects gaining traction (particularly in areas like K8s operations)
What fascinated me was the emergence of what Gartner calls “Generative AI natives” – vendors building their entire platforms around large language models rather than adding AI as a feature.
The Human Element Remains Critical A recurring theme across multiple sessions was that AI won’t eliminate the need for skilled I&O professionals – but it will change how they work. Today’s discussions highlighted three critical areas where human expertise becomes more crucial, not less:
- Novelty: Handling unique situations that AI hasn’t encountered
- Complexity: Understanding and managing intricate system interactions
- Variability: Adapting to changing conditions and requirements
The emphasis shifted from routine task execution to creative problem-solving and strategic thinking – skills that AI currently augments but cannot replace.
Portfolio Approach to Implementation One of the most practical takeaways came from the discussion of how to structure AI initiatives:
Within Boundaries:
- Focus on augmenting existing work patterns
- Build overall I&O engineering maturity
- Prioritize stability through mentoring by senior I&O staff
Pushing Boundaries:
- Transform work patterns with new approaches
- Monitor AI agent evolution
- Emphasize cross-disciplinary collaboration
Breaking Boundaries:
- Reimagine both work patterns and types of work
- Implement new skillsets and roles
- Prioritize creativity and innovation
Looking Ahead: The Future of I&O The vision of generatively adaptable systems by 2027 isn’t just about technology – it’s a fundamental shift in how we think about operations. The key components outlined in the sessions include:
- Dynamic intelligence that adapts to changing conditions
- Personalized interfaces that learn user preferences
- Composable architectures that can be reconfigured on the fly
- Connected data that provides real-time context
- Autonomous agents working in coordinated systems
- Integratable tooling that can be easily customized
Action Items for Our Team:
- Begin co-developing our AI vision within I&O
- Start the process to operationalize AI initiatives
- Implement a portfolio-based approach with investments across all categories
- Focus on building trust between human operators and AI systems
The quote that’s staying with me tonight: “AI will not eliminate the need for skilled I&O professionals – but it will replace those who don’t use it effectively.” It’s a powerful reminder that our challenge isn’t just implementing AI, but evolving alongside it.
Tomorrow brings an exciting mix of sessions, from “Supercommunicators” with Charles Duhigg to practical discussions on infrastructure modernization and hybrid cloud strategies. I’m particularly interested in the ITSM chatbot session – seems like we might see what’s beyond the current GenAI hype. More insights to come, assuming my brain hasn’t reached its AI saturation point!
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