GCC Intelligence Series · Energy & Natural Resources · v0.2 Feasibility

AgentShift Index

A Strategic Decision Enablement Framework for Agentic AI Transformation spanning both parent-operator and GCC role universes (~500 archetypes) — mapping AI agent impact, asset and jurisdictional anchoring, and a 5-way decision (Keep / Agent-Direct / Wait-then-Agent / Hybrid / GCC-Lift) into a Parent → GCC → Agent bridge for the Energy & Natural Resources sector.

The Core Framework

Every role is scored on two dimensions: Transaction Intensity — how repetitive, rule-based, and volume-driven the work is — and Decision Complexity — how much judgment, ambiguity resolution, and stakeholder navigation it requires. These combine into a single Agent Impact score on a 0–10 scale. Higher transaction and lower decision complexity produces a higher impact score. Each role then falls into one of three restructuring zones:

Agent-Core (8–10)— agent IS the worker, 60–80% FTE reduction

Agent-Augmented (5–7.9)— humans lead, agents on subtasks, 30–50% gain

Human-Core (0–4.9)— agents are peripheral tools, 10–20% uplift

Feasibility Classifier — the strategic question: for every role across the operator and its GCC, where should the work actually live?

Keep Onshore— OT/safety-critical, regulator-anchored, data-sovereignty (NOC seismic), or strategic asset-side leadership

Agent-Direct (skip GCC)— high impact + production-ready tooling, automate at parent (e.g. AP/AR, drilling-data QA, IT service desk)

Wait-then-Agent— hold onshore briefly, agentise at parent in 12–24 mo. Offshore setup costs don't pay back over that horizon.

Hybrid (GCC + Agent)— GCC as transformation lab, agents augment from day 1 (reservoir copilots, asset-integrity assistants, turnaround planners)

GCC-Lift (classic)— labour arbitrage still wins, AI peripheral — transactional, low-judgment, no asset/geo anchor

What’s Inside

8 Diagnostic Layers: Agent Impact, Transaction Intensity, Decision Complexity, Agent Readiness, Offshoring Potential, Feasibility (new in v0.2), Restructuring Mode, and Headcount Detail — each recolors and re-aggregates the treemap to reveal a different dimension of workforce exposure.

Two Role Universes: Toggle between Parent (~94 onshore archetypes across Houston / London / The Hague / Aberdeen / Stavanger / Singapore / Calgary), GCC (400 captive-centre roles), or Both. The Location filter rewires every chart, bridge, and economic calculation.

4 Sub-Sectors: IOC Engineering GCC (bp TSI, Chevron ENGINE, Shell STCB), IOC Transactional GCC (Shell SBO, bp FBT), National Oil Company (Aramco, ADNOC), and Renewables & New Energy Pure-Play (Lightsource bp, Iberdrola). Each reweights department footprint to match the actual operating model.

3 Transformation Layers: Savings Map, Capacity Released, Upskill Potential — trigger a scorecard + dual bridge (People + Economics, USD $M/yr).

Feasibility Layer: A 5-way classifier per role — Keep Onshore, Agent-Direct, Wait-then-Agent, Hybrid, GCC-Lift — driven by ENR-specific anchors (OT/safety-critical, asset proximity, geo-lock for sanctions and data sovereignty, HSE jurisdiction) plus readiness and impact. Adds a Parent → GCC bridge (Parent FTEs → Keep onshore → Agent-Direct at HQ → Wait-then-Agent → Movable to GCC → where Lift vs Hybrid lands) and three-stage economics (Parent cost → GCC cost → Agent cost).

Economics Tab: Deployment-wave timeline (Now / Next / Later) plus Azure-stack bottom-up cost model including an Industrial IoT row for historian/PI System integration, and an OT-Regulated build tier for IEC 61508/62443 functional-safety agents.

Adjustable sizing: GCC headcount (75–10,000+), Parent FTEs (2,000–300,000+), and average base CTC (USD). All math recomputes live.

How to Read the Treemap

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Rectangle = a role. Each tile represents one GCC role (e.g., AP Processor, IT Service Desk L1).

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Area = workforce share. Larger tiles = more people in that role as % of total GCC.

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Color = selected metric. Toggle layers to recolor: green (low impact) to red (high impact).

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Hover = full detail. Tooltip shows all scores, transformation model, upskill pathway, and target role.

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Filters = sub-sector, department, location. Narrow to IOC Engineering / IOC Transactional / NOC / Renewables, drill into a single function, or switch Location to Parent / GCC / Both to rewire the bridges and economics.

Start Exploring ↓

494 roles (400 GCC + 94 parent) across 17 departments

4 sub-sectors: IOC Engineering, IOC Transactional, NOC, Renewables & New Energy

5-way Feasibility classifier: Keep / Agent-Direct / Wait-then-Agent / Hybrid / GCC-Lift

3-stage economics: Parent → GCC → Agent run-rate (USD $M/yr)

Applicable to GCCs with 75+ employees; plug in your base CTC to convert cost bands

Layer

Transform

Low

High

GCC Size

Parent FTEs

Base CTC (USD/yr)

Location

Sub-Sector Department

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AgentShift Index — Methodology & Layer Definitions

This index adapts Andrej Karpathy’s US Job Market Visualizer for the Indian GCC context. Karpathy scores occupations on whether the work is fundamentally digital. For GCCs nearly every role is already digital, so the AgentShift Index replaces that axis with a transactional–decisional framework: each role is scored on how repetitive and rule-based it is, and how much judgment it requires. Higher transaction intensity and lower decision complexity produces a higher Agent Impact score. An Invoice Processor sits near the top of the scale and represents work where agents are the primary worker; a Data Scientist sits near the bottom and represents work where agents are peripheral tools. Entry-level roles (0–3 yrs) average around 8.0; senior roles (7–12 yrs) average around 3.9. The Transformation Model extends this into a full waterfall — cost pool, capacity released, agent cost, net savings, upskillable FTEs, and net headcount impact — with specific upskill pathways, certifications, and ramp times for every role transition.

Agent Impact Score

Primary index. Composite of T and inverse D. Rectangle area = workforce %. Color: green (low) to red (high).

0–1 Data Scientist • 4–5 FP&A Analyst • 8–10 AP Processor

Transaction Intensity (T)

How repetitive, rule-based, volume-driven, and SOP-adherent the work is.

0–1 Purely strategic • 4–5 Mixed • 8–9 High-volume, SOP-driven • 10 Pure transaction

Decision Complexity (D)

How much judgment, ambiguity resolution, and stakeholder navigation. Color inverted: red = low (automatable), green = high.

0–1 Zero judgment • 4–5 Policy interpretation • 8–10 Strategic/creative judgment

Agent Readiness

Tool maturity for this role. High impact + high readiness = immediate transformation candidate.

0–3 Early R&D • 4–6 Emerging • 7–9 Production-ready • 10 Off-the-shelf

Offshoring Potential

Combined: (a) parent→GCC migration upside + (b) GCC→agent displacement potential.

0–3 Fully offshored • 4–6 Partial • 7–10 Major opportunity

Feasibility

The strategic decision per role: where should the work actually live? A 5-way classifier driven by Agent Impact, Readiness, plus three ENR-specific anchors — OT/safety-critical, asset proximity, and geo-lock (sanctions, data sovereignty, HSE jurisdiction).

Keep: OT/SIS-anchored, regulator-anchored, or strategic asset-side leadership
Agent-Direct: high impact + production-ready tooling — automate at parent, skip GCC
Wait-then-Agent: agent inevitable but readiness lags — hold onshore, agentise in 12–24 mo
Hybrid: meaningful AI gain + human judgment — GCC as transformation lab
GCC-Lift: transactional, low-judgment, no asset/geo anchor — classic labour arbitrage

Restructuring Mode

Three zones based on Agent Impact Score.

8–10 Agent-Core: 60–80% FTE reduction
5–7.9 Agent-Augmented: 30–50% productivity gain
0–4.9 Human-Core: 10–20% efficiency uplift

Savings Map

Net savings per role are the value of capacity released, less the cost of deploying the agent. Colors show where the money is.

Capacity Released

FTEs freed by automation. Tiles show FTE count and automation %. Drives the transformation waterfall.

Upskill Potential

Affinity score (0–10) based on education headroom, skill adjacency, and target role availability. Green = high redeployability, red = displacement risk. Each role has a specific target role, certifications, trainings, and month-by-month learning path.

Cost model: Salary bands are multipliers of a base CTC unit (1x). Plug in your organization’s base (e.g., 1x = ‎₹4 LPA) to convert all figures to absolute ‎₹. Agent cost ratios range from 0.15x (mature tools) to 0.45x (early-stage). Upskill affinity scores factor in education headroom, skill adjacency, and target role availability within the same department.
Applicable to GCCs with 75+ employees. Adjust the GCC Size input above to model your organization.

Conversation Guide — ENR GCC AgentShift v0.2

v0.2 additions for client conversations:
• Feasibility layer — open with the 5-way distribution. Set Location to Parent (Onshore) to show the Parent → GCC bridge and Three-Stage Economics. This is the answer to "should we even open a GCC for this work?" — not the v0.1 question of "what does our existing GCC look like?"
• Sub-sector split — the IOC archetype is now two: IOC Engineering GCC (bp TSI, Chevron ENGINE, Shell STCB) and IOC Transactional GCC (Shell SBO Chennai, bp FBT). Use the right one — a Shell SBO conversation about subsurface is the wrong room.
• OT-Regulated build tier on the Economics tab — anticipate the process-safety pushback. DCS-adjacent agents need IEC 61508/62443 evidence, NOPSEMA/UK-HSE/BSEE/PSA sign-off. Build cost $400K–$1M, 24–48 month payback. Acknowledge it up front.

Designed for meetings with ENR GCC CXOs (Country Head, Head of Engineering, Head of Subsurface, Head of Asset Integrity, Head of Operations, Head of Transformation). Three scenario playbooks below, anchored on real Shell SBO/STCB, bp GBS/FBT/TSI/Digital Hub, and Chevron ENGINE structures.

Scenario 1: "Where should we invest in AI agents first?"

Setup (2 min): Open at All ENR Sub-Sectors. Department treemap shows 17 functions. SIZE = workforce share. COLOR = avg agent impact. Finance & Accounting and Technology dominate by headcount (the Shell SBO / bp FBT footprint), but Subsurface, Wells, and Refining show distinctive ENR talent concentrations that have no banking equivalent.

Discovery (5 min): Ask: "Where does your India centre actually deliver work today — finance only, or are you also doing engineering and subsurface?" Click that department. Red/orange tiles = Agent-Core and Agent-Augmented targets.

Quantify (5 min): Switch to Savings Map. Enter their GCC headcount. Waterfall shows: cost pool → capacity released → agent cost → net savings → upskillable FTEs.

Close (3 min): Switch to Upskill Potential. Show that most freed roles have viable pathways. Position the KPMG engagement: automation + workforce transformation.

Scenario 2: "We are bp / Shell / Chevron — show me our view"

Filter: Select Integrated O&G Major. Subsurface, Wells, Asset Integrity, Refining swell. This mirrors what bp TSI / Chevron ENGINE actually deliver from India.

Key point: "Most consultants will tell you to automate F&A in your SBO or FBT centre. That is table stakes — Shell has been doing it for a decade. The real opportunity is what bp TSI and Chevron ENGINE are already proving: subsurface modelling, turnaround planning, asset integrity, and digital twins delivered from India for global hydrocarbon and new-energy assets, at 30% of the cost of doing it in Houston or London."

Scenario 3: "Build the business case"

Full waterfall: Set GCC Size to their headcount. Capacity Released layer. Walk through each stat: FTEs freed (25-35% — wider range in ENR than banking because of the technical core), Upskillable (60-75%), Net Savings (cost reduction after agent costs). Remind them all numbers are v0.1 illustrative until validated against their actual GCC role inventory.

Close: "This is a diagnostic view. The next step is a 4-week deep-dive where we map YOUR role inventory, validate scores against your process data, and build a sequenced transformation roadmap."

Data Confidence (internal use)

• Source: 400-role ENR taxonomy across 17 departments and 3 sub-sector archetypes (Integrated O&G Major / NOC / Renewables Pure-Play). Department structure anchored on publicly disclosed Shell SBO/STCB, bp GBS/FBT/TSI/Digital Hub, and Chevron ENGINE structures (2024–2025 press releases and careers sites).

• T/D scores: KPMG estimates from department context and role patterns. v0.1 ILLUSTRATIVE — LOW-MEDIUM confidence. Must be validated against actual client GCC job catalogue before use in delivery.

• Workforce %: KPMG estimates. The relative shape (technical core vs. F&A vs. tech) is anchored on bp TSI / Chevron ENGINE / Shell SBO public disclosures; specific percentages are illustrative and require validation.

• Upskill paths: Based on KPMG workforce transformation frameworks. Target roles, certs, ramp times are indicative.