# Aleksandar Rodic

Aleksandar Rodic writes about how energy, AI infrastructure and data sovereignty shape business and investment decisions. Rodic's posts connect developments such as European fuel supply and data-centre expansion to their practical effects on companies, governments and industry.

- Profile: https://b2binfluencer.marketing/creators/aleksandar-rodic/
- LinkedIn: https://www.linkedin.com/in/alex-rodic-aleksandar
- LinkedIn followers: 6,988
- Topics: artificial-intelligence, ai-infrastructure
- Based on 11 dated posts, latest 2026-10-01

## Summary

They are most useful for briefings on how energy, AI infrastructure and data sovereignty affect business and investment decisions.

- Best for: An infrastructure investment firm briefing on AI compute, energy security and data sovereignty.
- Not for: Paid LinkedIn series for consumer retail brokerages seeking broad investor sign-ups.
- Check first: Confirm a recent briefing recording, audience data, and format, availability and terms.

### Takeaways

- AI is becoming an infrastructure race, not just a model race.
- Data sovereignty, not model quality, is the next enterprise AI battle.
- Fuel costs are a business problem that travels to the supermarket.

## Main ideas

- **AI is becoming an infrastructure race, not just a model race**: Rodic argues the AI competition is shifting to physical inputs and jurisdiction: electricity, land, grid connections, data centres, cooling, chips and regulatory approvals. Every model depends on physical infrastructure, and where that infrastructure sits increasingly matters. Boards should ask where data is stored, where inference happens, who controls the infrastructure, which laws apply and whether the power supply can support the load. Countries with abundant, reliable energy and predictable regulation gain an advantage; markets with constrained grids or slow approvals lose it.
- **Data sovereignty, not model quality, is the next enterprise AI battle**: Rodic argues that sophisticated buyers are starting to define the conditions under which AI can enter their most valuable workflows. Commercially, this matters more than the public debate about slowing frontier AI. Procurement is moving toward architecture-level guarantees: data residency, zero retention, model isolation, identity, access control, auditability and contractual control over intellectual property. The winning enterprise stack may not be the smartest public model, but the system institutions can trust with their most sensitive data, favouring sovereign and private AI infrastructure, secure cloud, zero-trust, model gateways and governance providers over model vendors that need broad data access.
- **Energy security now constrains rearmament, AI and industrial competitiveness at once**: Rodic's gas post starts with a storage shortfall and makes a broader point: Europe's plans to rearm, expand AI and data-centre infrastructure, and remain industrially competitive with China all depend on reliable, affordable power. Higher energy costs can weaken manufacturers and influence where factories, semiconductor plants and data centres are built. Defence production also needs dependable electricity for metals, chemicals, machinery, electronics and munitions. He names US LNG exporters, storage operators, power producers, grid developers and efficiency providers as potential winners, and European energy-intensive industries, defence manufacturers exposed to input costs and price-sensitive Asian importers as losers.
- **Fuel costs are a business problem that travels to the supermarket**: Rodic treats a diesel price move as an operating problem rather than a commodity story. Diesel moves trucks, construction equipment and agricultural machinery, so a higher fuel bill passes through transport contracts, food, construction and logistics and eventually reaches supermarket prices. Their key distinction is between temporary shocks that companies can absorb and permanent costs they cannot absorb indefinitely. Rodic also draws a line between large firms with hedging teams, purchasing power and capital access and smaller operators who have far fewer options, and ends with a direct policy point that Europe should remember smaller businesses when energy policy is discussed.
- **A repeatable method: translate the news into winners, losers and a watch list**: Across the posts, Rodic uses a consistent structure: a headline claim, an explanation of why it matters, board-level implications, who gains and loses power, commercial or investment relevance, and a short watch list. The writing targets decision-makers who need the business consequences of an energy, AI or policy development, not the technical detail. The interpretation is the product: several posts draw on reporting by Reuters and other outlets, which Rodic frames as questions about where factories, data centres and capital will go.

## Work to read

- [AI Compute Is Becoming Sovereign Industrial Infrastructure](https://www.linkedin.com/posts/alex-rodic-aleksandar_artificialintelligence-infrastructure-activity-7505940620176384000-JpCP)
- [AI's Next Enterprise Battle Is Data Sovereignty, Not Model Quality](https://www.linkedin.com/posts/alex-rodic-aleksandar_ais-next-enterprise-battle-is-data-sovereignty-activity-7505580036414996480-7GSP)
- [Europe Is Entering Winter With a Strategic LNG Vulnerability.](https://www.linkedin.com/posts/alex-rodic-aleksandar_energy-europe-activity-7506291834139238400-qS6Q)
- [Diesel is becoming a business problem again.](https://www.linkedin.com/posts/alex-rodic-aleksandar_diesel-is-becoming-a-business-problem-again-activity-7511335710608625664-hDvD)

## Partnerships

The four posts by Aleksandar Rodic offer analytical commentary on energy security, AI compute and data sovereignty. None carries a sponsorship disclosure, branded-post label, sponsored series, media kit, rate card or stated partnership or booking route. They do not specify what a paid engagement would involve, its cost or available formats. For an institutional briefing, contact Rodic through the LinkedIn account and ask about format, availability and terms; these are not stated in the posts.

## Alternatives

- Simon Allen: Choose Simon Allen when the session is about how the build gets delivered rather than why it is happening. Allen co-founded the Quantum Infrastructure Council and moderates Capacity Europe 2026's panel "Scaling Under Scarcity: Delivering Projects Amid Shortages", which examines power equipment, chips, cooling, supply chains and skilled resources — the constraints that decide whether a project lands on time. Aleksandar Rodic's posts treat planning reform, grid constraints, regional growth, investment appetite and supply-chain delivery as UK-specific problems, and connect quantum readiness to power, cooling, site design and long-term strategy. If the client's question is who can deliver this in the UK and what is slowing them down, Allen is the closer fit for the same briefing slot.
- Michael Freedman: Choose Michael Freedman when the audience is technical and the question is how compute and the physical plant became one system. Freedman's background is in distributed systems, networking and storage — server utilization, network bisection, storage placement, scheduling and cluster orchestration. Aleksandar Rodic's posts explain why power moved from an optimisation variable to the binding constraint: hyperscalers denying server expansion because of regional power limits, an operational control loop responding to thermal and workload conditions, and the shift from air to liquid cooling. Freedman speaks at the Ignition Community Conference with Tiger Data and Inductive Automation about industrial control plus Postgres at the scale of the physical world. For a briefing aimed at engineers, operators or a data-platform team, this is the deeper systems account.
- Eric Victor Gitter: Choose Eric Victor Gitter when the session should be about where the money goes outside silicon. Aleksandar Rodic's posts break the roughly $6.7 trillion spend to build AI-ready data centres by 2030 into its non-compute halves — power infrastructure at 15–25% against 5–10x rack power density, a $1.3 trillion utility capital call, cooling at 10–15% as the second-largest capital expense, and about $800 billion in facilities build-out. The Stargate post reads OpenAI's memory deals with Samsung, SK hynix and Micron as the hyperscalers locking up inputs long term, and describes the market splitting into companies that work with hyperscalers and everyone else. If the client wants the supplier map and who wins the non-silicon spend, this is more directly on point than a compute-and-sovereignty session.

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AI-assisted summary of public posts. Audience demographics are not available. Engagement appears only where we checked recent posts. Method: https://b2binfluencer.marketing/methodology/