Energy Gang: "The Connected World of Energy"

Special Episode from Wood Mackenzie
Date: October 14, 2025
Host: Ed Crooks (Wood Mackenzie, Vice-Chairman of Energy)
Guests: Jason Liu (CEO, Wood Mackenzie) & Sunayana Ojalan (Equity Analyst, Bernstein; former Head of Strategy/Climate at Hess)

Episode Overview

This special Energy Gang episode dives into the findings and themes from Wood Mackenzie’s new book, Connected, co-authored by CEO Jason Liu and Chief Analyst Simon Fryers. Host Ed Crooks is joined by Liu and first-time guest Sunayana Ojalan to examine the ever-increasing complexity in energy markets, the need for new paradigms of planning and decision making, and the powerful role of AI and data. They probe the language, challenges, and opportunities of the "energy transition"—or as the guests increasingly call it, "energy evolution"—asking how companies, asset managers, and policymakers should navigate a future of ever-greater uncertainty, interconnectedness, and opportunity.

Key Discussion Points & Insights

1. Guest Introductions & Career Pathways

[00:45]–[04:48]

• Jason Liu shares his lifelong connection to energy, from wind farm family vacations to leading software and AI at major firms. Newly arrived at Wood Mackenzie, he brings an “outsider’s perspective”, marrying tech and energy.

  • “I think that's part of the outsider's perspective that I think I could help bring to the energy world—how does energy meet tech and AI?” (Jason Liu, 01:42)

• Sunayana Ojalan recounts her chance entry into energy with technical and strategic stints at Schlumberger and Hess, culminating in energy equity analysis at Bernstein. She highlights her new vantage point—advising markets rather than running assets.

  • “I joined energy by accident, but stayed by choice.” (Sunayana Ojalan, 03:06)

2. Why Is the Energy Landscape So Complex Now?

[04:48]–[08:27]

• Liu: The past decade has brought exponential increases in complexity—rising demand, energy transition, increased regulatory and national security pressures.

  • Industry confidence in forecasting, even short-term, has collapsed. Old models are “broken.”
  • “There was just a lack of predictability… not just 5, 10, 15 years out, but even over a six to nine-month period.” (Jason Liu, 05:08)

• Crooks: Uncertainty isn’t just a cliché—interconnection between policy, tech, climate, and global markets is real and unprecedented.

• Liu: AI demand is a “hockey stick” question; real-world grid and capacity constraints complicate planning.

3. The Four Forces and Deeper Operational Challenges in Energy

[08:39]–[12:04]

• Ojalan: Four foundational forces in energy—geopolitics, policy, tech, supply/demand—constantly interact.

  • Companies must build “exit ramps” for pivoting as conditions change.
  • Oil & gas faces specific “decline curve” challenges: “Every barrel we produce was our best barrel; we have to replace it.”
  • Infrastructure’s long time horizons amplify the risk of obsolescence due to shifting futures.

• Liu: European energy majors’ push into renewables led to $80bn in lost value—cautionary tale of misjudged transition bets.

  • Changes in gas pricing and regulation (e.g., policy shifts like the Inflation Reduction Act) complicate even day-to-day decisions for US power developers.

4. “Energy Transition” vs “Energy Evolution,” and Why Language Matters

[12:04]–[17:24]

• Crooks: Language shapes decisions; “energy transition” implies a clear, unidirectional shift—but is it accurate?

• Liu: Wood Mackenzie now frames it as “energy evolution” or “energy addition”—not flipping a switch:

  • “There's an insatiable appetite for new energy ... and that will drive further increases in demand ... It's not a light switch, it's more of a dial.” (Jason Liu, 13:06)

• Ojalan: Energy’s growth is intimately linked to GDP, and each energy source’s trajectory is unique.

  • Oil demand growth is slowing, not reversing; gas demand is rising due to AI, manufacturing, and climate-driven cooling needs.
  • Some technologies are ready now (solar, wind, storage); others (nuclear, green hydrogen) are “2035-ish” prospects.

• Liu & Ojalan: Over-indexing on climate or national security creates regional divergences—Europe, China, and the US each have different priorities and strategies.

5. Integration, Not Siloing: The New Model

[17:24]–[19:46]

• Liu: The sector must move beyond siloed, “transition” thinking—energy sources, technologies, and policies are now inextricably connected.

  • “They're all integrated ... now I think everyone sees that the interdependence ... is all interrelated.” (Jason Liu, 16:15)

• Crooks & Liu: Market players, especially in the US, are shifting towards “integrated energy plans”—bundling solar, storage, and natural gas to meet reliability, policy, and commercial needs.

6. When and Why Energy Companies Diversify—A Hess Case Study

[19:46]–[23:40]

• Ojalan describes how, faced with the net-zero imperative (2019+), Hess explored three solution pillars:

  1. Decarbonizing operations.
  2. Adjacent technologies (esp. CCS—carbon capture and storage).
  3. Financial/off-balance offsets for residual emissions.

• Their ultimate strategy: stick to their core ("your knitting"), pursue realistic adjacencies (like CCS in regions where they operate best), and avoid headline-chasing diversification where they lacked competitive edge.

7. The Critical Role—and Pitfalls—of Energy Data

[23:40]–[30:55]

• Liu: “Bad data leads to bad decisions.” Three recurring mistakes:

  1. Underusing available data: Linear, human-driven models miss patterns.
  2. Overreliance on synthetic data: Modeled/AI-generated data is only as reliable as its inputs and can’t replace regulatory nuance or field-level insight.
  3. Siloed data: Integrated, cross-vector analytics are essential.
  • “We have the most proprietary data of anyone out there... We see this as an arms race.” (Jason Liu, 24:07)

• Wood Mackenzie has invested heavily in expanding its real data network—sensors, drones, IoT, satellites, human-collected regulatory information.

• Ojalan: For companies, effective planning requires integrating disparate oil, gas, EV, critical minerals, and climate datasets. AI can:

  • Augment scenario analysis to update outlooks quickly.
  • Enable global teams to collaborate on complex models in real time.
  • Reveal and mitigate model bias.
  • Free up talent for higher-level judgment ("AI can ... augment, but not replace, judgment.").

• “If we're going to be in this new world of using less people to do more ... companies ... leveraging data sets correctly will be differentiated.” (Sunayana Ojalan, 27:48)

8. AI & “Hyper Modeling”: Revolutionizing Decision Support

[30:55]–[35:10]

• Liu:

  • Enhanced scenario analysis: AI enables millions of real-time scenarios, shrinking reaction time from weeks to hours.
  • Integrated modeling: Different contexts need different tools, orchestrated via AI.
  • Prompt-based AI democratizes modeling: Executives, not just quants, can interrogate models directly.
  • Hyper modeling: AI tests and selects the best modeling approaches on the fly, raising predictive agility, and assembling “orchestras” of fit-for-purpose models.
    • “Hyper modeling ... now you can use AI to test these models real time ... you actually use an AI-suggested model ... That's a game changer.” (Jason Liu, 34:53)

• Wood Mackenzie’s Synoptic: The firm's umbrella AI initiative, aiming to integrate the best predictive and analytic monitoring into their offerings.

9. Practical Advice: How Should Leadership Respond to This New World?

[35:53]–[38:00]

• Liu’s “Winning Trifecta”:

  1. People: Recruit and retain leading expertise.
  2. Data: Harness the largest and best-quality datasets.
  3. AI: Embed advanced decision-support across all levels.

• Holistic Integration: Think like a family doctor: know the whole system, not just isolated organs or symptoms. Don’t silo assets, functions, or analysis.

  • “The way you engage with your doctor … you could try to go to specialists on everything or ... have someone provide a holistic view … Right now, the world is too siloed.” (Jason Liu, 36:15)

10. Portfolio/Asset-Level Scenario Analysis: Beyond Forecasting

[38:00]–[41:31]

• Ojalan: The real value lies in scenario analysis at BOTH the asset AND portfolio level. The goal isn’t prediction, but resilience and agility.
  • Asset-level understanding plus holistic integration enables quarterly results to serve as communication, not frantic recalibration:
    • “Winners are going to be folks who manage across all three ... resilience from hydrocarbons, growth from low-carbon tech, using AI for adaptation.” (Sunayana Ojalan, 38:42)

11. Agility & Opportunity: The Glass Half-Full

[41:31]–[43:14]

• Liu: Success depends on agility, not only prediction. Over $75 trillion is likely to move in the energy evolution—huge opportunity for those who get it right.
  • “There will be well over $75 trillion invested ... and that presents massive opportunity ... for those that get it right.” (Jason Liu, 42:05)
• Ojalan: Energy is more exciting than ever; capital is shifting from inefficient, philanthropic flows to more economic, results-driven public investment.
  • “This is actually the best time for the sector ... better understanding of the economics as well, without the subsidies.” (Sunayana Ojalan, 42:44)

Notable Quotes & Memorable Moments

• On the shift from "transition" to "evolution":
  • “It's not a light switch, it's more of a dial.” (Liu, 13:06)
• On the modeling revolution:
  • “Now you can use AI to test these models real time ... That's a game changer.” (Liu, 34:53)
• On data pitfalls:
  • “Bad data leads to bad decisions.” (Liu, 23:40)
• On scenario planning:
  • “The benefit of scenario planning is not about predicting the future. It’s about looking at a plausible set of futures.” (Ojalan, 38:42)

Essential Timestamps

• 00:45 – Meet the guests: Jason Liu’s career path and role at Wood Mackenzie
• 03:06 – Sunayana Ojalan’s entry into energy and shift to asset management
• 05:08 – Complexity and unpredictability: What's fundamentally changed in energy
• 12:04 – Rethinking “energy transition” vs “energy evolution”
• 17:24 – How sector integration is supplanting old “siloed” models
• 19:46 – Hess’s real-world decisionmaking on decarbonization and adjacent tech
• 23:40 – The “bad data” trap and building quality, integrated data systems
• 27:48 – How data and AI are reshaping strategic planning and bias control
• 30:55 – AI’s four breakthroughs and the rise of “hyper modeling”
• 35:53 – The “winning trifecta”: people, data, AI, plus holistic integration
• 38:42 – Asset and portfolio-level scenario analysis for resilience and agility
• 42:05 – The $75 trillion investment opportunity

Tone & Closing Thoughts

The episode is a dynamic, forward-looking conversation rooted in operational realism and strategic optimism. Both guests stress the necessity—and promise—of adaptation, not just prediction: agility, integration, and open-mindedness will differentiate both companies and countries. They point to a massive, multi-trillion dollar opportunity for those who rethink old paradigms and embrace the power of holistic analysis, quality data, and AI.

The final consensus: this is the most exciting, challenging time to work in energy. Those who innovate, integrate, and invest wisely will not just survive, but thrive.

For further insights, listeners are encouraged to download Wood Mackenzie’s book "Connected" at www.woodmac.com.