All 269 resources by section

Google Cloud◆

Google’s agentic AI transformation framework

Google Cloud's operational framework: vision, an agentic development lifecycle, and the capabilities underneath, with owners named at each stage.

McKinsey & Company◆

Agentic AI change leadership

Records the reasoning directly: if the agent gives the wrong answer and the employee acts on it, it is still the employee's mistake, so people are reluctant to rely on tools they do not fully understand where accuracy, professional judgment and reputation are on the line.

UST◆

CIOs guide to agentic AI

Sets out a specific task-level set - completion rate, work reduction, cost and cycle time per task, safety violations - explicitly in place of technical model scores, which are equally unrelated to whether work got done.

Cloud Security Alliance◆

Defining non-human identity

Notes that non-human identities are created by systems rather than business processes and run continuously without direct human oversight: a person reading a screen and pausing between actions creates natural moments to catch a mistake, while an identity executing thousands of operations a second offers no such window.

Boston Consulting Group

Preparing for an AI-first future

BCG on what separates firms already operating AI-first from those still planning to, drawn from more than 70 companies.

Deloitte

Scaling agentic AI: from pilots to production

Why agentic pilots stall short of production, and the architecture Deloitte and Google Cloud propose for getting past it.

Deloitte◆

Strategic governance of AI

Positions independent assurance over AI as an emerging oversight responsibility for audit committees rather than a delivery-team function.

IBM◆

Agentic AI risk and opportunity

IBM on governing agents in regulated settings, comparing emerging Australian and EU regulatory approaches.

IBM◆

C-suite synergies for AI ROI

Reports 36% higher AI ROI for Chief AI Officers running hub-and-spoke or centralized operating models than for those managing decentralized ones, and roughly twice as many pilots reaching production, from a survey of more than 600 such officers fielded in the first quarter of 2025.

UC Berkeley◆

An AI governance maturity matrix for boards

Names shortage of AI knowledge among board members as one of the most common hindrances to robust AI governance; oversight becomes cursory and directors defer to management.

AWS◆

Governance, risk and compliance for responsible AI in financial services

Widens the picture by listing what a regulated firm is already tracking, and the length of that list undercuts the idea of three blocs - though the items are not equivalent regimes. In the United States alone it names a federal executive order, a federal bill, the NIST framework, a securities regulator notice, statutes in Colorado and Texas, and a privacy regulator's automated decision-making rules in California. The United Kingdom appears not as a statute but as a government department and two regulators publishing separately. Asia-Pacific carries national laws in South Korea and Japan, Australian guidance alongside a voluntary safety standard, a Singapore consultation aimed at financial institutions, two Hong Kong publications and an ASEAN guide. The list is offered as non-exhaustive and omits China entirely, so it is a picture of the tracking burden rather than a census.

Deloitte

State of AI in the boardroom

Deloitte's survey of 695 board members and executives on how far AI has moved onto the board agenda.

Boston Consulting Group◆

Driving cost advantage with AI

BCG's executive perspective on structural cost advantage, and why copilots layered on unchanged processes fail to deliver it.

Deloitte◆

Navigating AI spend dynamics

Deloitte's 28-page analysis of token economics: what drives spend, and where owned infrastructure overtakes metered APIs.

OpenAI◆

A scorecard for the AI age

Proposes a concrete measure that separates working systems from demonstrations: count only tasks meeting the quality bar, divide full cost - including employee time, human review, retries and rework - by that number, and track results as ready to use, needs correction, or needs escalation.

Infosys

AI token economics for executives

Infosys on governing AI cost: observability first, then routing, then enforced guardrails and workflow budgets.

Accenture

Accenture Tokenomics

Accenture's argument for tokenomics as a C-suite discipline, jointly owned by the finance and technology functions.

Boston Consulting Group

Return on AI: What CEOs need to know

BCG's return-on-AI framing for chief executives, including the margin comparison against AI-native products.

Boston Consulting Group◆

AI value creation in leading enterprises

BCG's account of where AI value actually landed in leading enterprises, and the investment pattern behind it.

Anthropic◆

Building multi-agent research

Anthropic's engineering account of taking multi-agent research from prototype to production, including evaluation method.

Uber◆

Uber - Journey to Generative AI

Describes investing in production capabilities including safe model deployment and automatic model retraining, and tooling that measures model quality across all stages, precisely because manual maintenance does not scale.

Google Cloud

L’Oreal - Launching GenAI as a Service in 3 Months

How L'Oréal stood up a generative AI service for 90,000 employees in three months, with the architecture described.

Capgemini

Proposal AI agent

Capgemini on building a proposal-generation agent for insurance tenders, with the cost profile of running it.

OpenAI

Multi-agent investment research

OpenAI's worked example of specialist agents reporting to a coordinating manager, using the agents-as-tools pattern.

Boston Consulting Group

Playbook on the future of marketing

BCG's executive playbook on the marketing function: where generative AI changes content economics and brand control.

Boston Consulting Group

Playbook on AI in procurement

BCG's procurement playbook, including the category-level savings ranges and the buyer capacity they assume.

Capgemini

AI playbook for CMOs

Capgemini's CMO playbook, drawn from roughly 1,500 organisations, on building rather than buying marketing capability.

World Economic Forum

Green CPO AI playbook

The World Economic Forum's procurement playbook, focused on supply-chain risk and sustainability rather than cost alone.

Boston Consulting Group

Guide to hiring AI-first CMOs

BCG on what chief executives should look for when hiring a marketing leader expected to operate AI-first.

Boston Consulting Group

Supply Chain playbook

Genpact◆

$18 trillion in trapped AI value

Genpact and HFS on four interlocking enterprise debts, sized individually and modelled for what resolution is worth.

Boston Consulting Group

640 CEOs on AI

BCG's annual survey of 640 chief executives on AI investment intent and where it is actually going.

Capgemini

How AI’s reshaping CXO decisions

Capgemini on how far AI has reached executive decision-making, and the gap between individual and collective use.

EY

CEO Outlook Survey AI

EY-Parthenon's CEO outlook, covering growth expectations and the transformation agenda behind them.

KPMG

2026 CEO Outlook AI

PwC

2026 CEO Survey AI

Anthropic◆

Anthropic’s CISO guide to agentic AI

Anthropic's deputy CISO on the four questions his team asks before approving any agentic use case.

Microsoft

Digital defense report

Microsoft's annual threat intelligence report on how attackers and defenders are both adopting AI.

World Economic Forum

Elevating cybersecurity: the CISO agenda

The World Economic Forum on the CISO's widening remit and the economics behind it.

Accenture

State of cybersecurity

Accenture's security survey of 2,286 companies on the distance between perceived and demonstrable readiness.

Anthropic

Threat intelligence report

Anthropic's threat intelligence reporting on observed misuse patterns and the techniques behind them.

Boston Consulting Group

Securing finance ROI

BCG on why finance functions land well below their AI return targets, and how few executives can quantify the return at all.

OpenAI◆

Security incident during model evaluation, with Hugging Face

Records that both sides found the activity independently and began containing it - while itself treating that detection as insufficient, since the monitoring in place during internal testing is named among the things to strengthen and the systems had already gained network access, escalated privilege and reached a third party's production database before anyone noticed.

AWS◆

Navigating the security landscape of generative AI

Argues the opposite of consolidation: train people inside the delivery and data science teams to run their own reviews and to recognise when to escalate, on the reasoning that a single central function becomes the gate every review waits at, and that each hand-off across an organizational boundary costs something. Offers its own internal programme as the worked example, and is explicit that the posture has to be enablement rather than refusal.

Cloud Security Alliance◆

Agentic AI Identity and Access Management

Proposes an identity and session model in which a revocation is notified once and every enforcement point consults shared state, so that a terminated agent is blocked across protocols and integrations rather than per system.

CISA◆

Careful adoption of agentic AI services

Names the pattern precisely: someone with low privilege induces a high-privilege agent to do what they could not do themselves, and because the action genuinely executes under the agent's trusted identity, the record it leaves reads as legitimate and pushes detection further out. Adds the credential half - keys and tokens that are static, shared between agents, or weakly held let an attacker act as the agent rather than merely through it, which defeats behavioural guardrails and the monitoring tuned to normal behaviour at the same time.

NIST

AI Risk Management Framework 1.0

Proposes that regular assessment involve internal experts who were not front-line developers on the system, or assessors outside it entirely, with people beyond the building team consulted in proportion to the risk being carried.

NIST

AI Risk Management Framework Playbook

Proposes the artefact whose absence this issue is about, and is specific about what it has to cover: policies for taking an AI system out of service that address user and community concerns and reputational risk, business continuity and financial exposure, dependencies both upstream and downstream, retention and other regulatory duties, and the possibility of a later legal, regulatory, security or forensic investigation. Separately asks that contingency processes for mission-critical systems be verified to include deactivating them - verified, not merely documented. It stops short of naming who holds that authority, which is the part still resting on our own reading.

Deloitte

Physical AI’s moment of acceleration

Deloitte on embodied AI reaching commercial viability, with four maturity stages and a governance constraint.

EY

Five forces redefining CTO mandates

EY on the five forces reshaping the CTO mandate in software businesses, including a notable security readiness gap.

IDC

CEO AI Perspective

IDC's short executive read on the chief executive's view of AI and skills.

PwC

AI leadership playbook overview

PwC's leadership overview covering governance parameters, ethics and trust as operating constraints.

OpenAI

Guide to staying ahead with AI

OpenAI's leadership guide, tracking capability, cost and adoption curves and what embedding training into daily work changes.

Forrester

CIO’s guide to AI readiness

Carnegie Mellon SEI◆

The AI Adoption Maturity Model

Carnegie Mellon SEI with Accenture: five maturity levels across eight dimensions, with evidence artefacts.

EY

Vision for the CHRO in year 2030

EY's projection of how the chief HR officer's remit changes by 2030.

PwC

Two futures of jobs in the AI era

PwC's labour-market analysis built from over a billion job advertisements across six continents.

Accenture

Reinventing talent for the AI era

Accenture's talent research, identifying the minority of organisations taking an integrated human-AI approach.

Boston Consulting Group

HR playbook

BCG's HR playbook covering role disruption and the near-term productivity and cost effects.

Boston Consulting Group

To invest in and upskill people

Frames capability investment as the route through, which addresses competence but not the accountability question underneath it.

Capgemini

The blueprint to scaling AI for business transformation

Capgemini's method for scoring how amenable a function is to generative AI, and what blocks adoption.

Deloitte

Unlocking the right agentic AI use cases

Deloitte's qualification method for agentic suitability, including its differentiability index.

Anthropic

Building trusted AI in the enterprise

Anthropic's guidance on selecting use cases, with the data and success metrics each requires.

Boston Consulting Group

The gen AI transformation of the communications function

BCG's approach to assessing opportunity by task, covering automatability and the productivity ceiling.

Deloitte

State of generative AI in the enterprise

Deloitte's quarterly enterprise survey, here on proliferation and the governance that has not kept pace.

OpenAI

Identifying and scaling AI use cases

OpenAI's impact-and-effort method for prioritising use cases, drawn from customer success practice.

Deloitte

Deloitte’s AI playbook for CXOs

Deloitte's role-by-role playbook setting out what each C-suite officer owns in an agentic programme.

KPMG

Value at Stake

KPMG's quantification of generative AI value at stake, modelled across more than 7,000 companies.

Microsoft

Microsoft’s AI transformation playbook

Microsoft's methodology for becoming a frontier firm, built around five elements from strategy to safeguards.

Boston Consulting Group

The AI-first Chief Transformation Officer

BCG on what chief executives should expect from a transformation officer operating AI-first.

Boston Consulting Group

CEO playbook on maximizing AI value

BCG's executive perspective on maximising AI value, covering starting points and capability building.

Deloitte

Sharpen your GenAI strategy

Microsoft

A thousand customer transformation stories

Microsoft's running collection of customer transformation stories across employee and customer experience.

Capgemini

54 gen AI use cases across engineering, manufacturing and service

Capgemini Research Institute's cross-sector use case collection, drawn from around 1,100 organisations.

Google Cloud

30 agentic AI use cases across Finance, Healthcare, Tech, CPG+, and more

Google Cloud's agentic use case analysis across finance, healthcare, technology and consumer sectors.

McKinsey & Company

60 AI case studies across Technology, Media & Telecoms, and more

A sector library for technology, media and telecoms, pairing deployment patterns with value estimates.

Google Cloud

601 gen AI use cases from industry leaders

A catalogue of named-customer deployments sorted by agent type: customer, employee, code, data and security.

EY

15 AI deployments across innovation and efficiency

Gartner◆

Build, buy or blend

Gartner's short framing of build, buy or blend as a deployment decision.

KPMG

Build-buy-borrow decision

Observes that fear of being left behind led many companies to buy off-the-shelf solutions, and expects more building - in-house or with partners - as organizations mature, laying out a decision grid across strategic fit, data sensitivity, customization, governance, integration, cost and skills.

Boston Consulting Group

Build-or-buy dilemma

BCG's earlier treatment of the build-or-buy question, focused on where proprietary data justifies building.

IDC

Enterprise build vs. buy

IDC's perspective on build versus buy for enterprises assembling AI-ready infrastructure.

MIT Sloan

Enterprise AI framework

MIT Sloan's framework for choosing between buying, boosting and building generative AI capability.

WorkFusion

Build vs. buy

McKinsey & Company◆

Data readiness for scaling AI impact

States that one answer can be assembled from fragments of many documents at once, so the trail is not straightforward, and identifies unstructured data entering and exiting AI systems with little traceability as a major challenge.

Accenture

AI-ready cloud strategies

Accenture on why cloud programmes declared finished are not, drawn from 216 companies.

Boston Consulting Group

Data & Digital Platforms playbook

BCG on evolving the data and platform stack for AI, drawn from a survey of around 1,000 respondents.

EY

Study on CFO productivity growth

EY's study of how finance leaders are converting AI investment into measurable productivity.

Palantir

AI sovereignty is your alpha

Palantir's fifteen-step blueprint for retaining institutional control across the model, compute and control layers.

McKinsey & Company

Sovereign AI for resilience and impact

Deloitte

Elements for scaling gen AI

Deloitte on the elements that separate organisations scaling generative AI from those stuck experimenting.

Boston Consulting Group

BCG AI playbooks for senior executives

BCG's collected executive playbooks, organised by function for senior leaders.