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There’s considerable debate about the current state of agentic AI. Is the hype outpacing reality, or are we actually further along than many realize?

Since the previous edition, we've reviewed hundreds of the latest agentic and gen AI best practices, case studies, and innovation insights. Here’s the top 1%...

In today’s edition:

• Accenture CAIO: Multi-agents beyond the hype.

• Forrester CEO: Incumbent tech is scrambling.

• McKinsey unpacks AI-quantum synergies.

• QuantumBlack shares MCP reuse progress.

• Transformation and technology in the news.

• Career opportunities & events.

Read time: 4 minutes.

BEST PRACTICE INSIGHT

Accenture CAIO: Multi-agents beyond the hype

Brief: Accenture Chief AI Officer (CAIO) Lan Guan unpacks how the evolution from simple prompting to mutli-agent systems is faster than expected. The question now is not if, but how quickly enterprises can scale value.

Breakdown:

• Stage one of AI’s recent evolution is reactive: task processors for summarization or retrieval (80% of Accenture’s 2,000 AI projects)

• Stage two introduces single agents on top of LLMs, adding planning, reasoning, and tools for action. Alone, they aren't truly transformative.

• Stage three is multi-agents: specialized agents coordinating like human teams. It requires orchestration, memory, and enterprise integration.

• Though often seen as distant, new protocol standards like MCP and A2A signal multi-agent maturity, enabling interoperability and scalability.

• As with mobile apps after Apple and Google introduced SDKs and standards, agentic AI is now at an inflection point for rapid development.

Why it’s important: The rate of change and adoption for multi-agent systems is much faster than anticipated, especially due to convergence around standards. Enterprises need to understand their maturity and invest in the right capabilities now, so they don’t get left behind.

CEO INSIGHT

Forrester CEO: Incumbent tech is scrambling

Brief: Forrester CEO George Colony shared how AI will reshape the tech industry as newcomers offer cheaper, more adaptable solutions, while incumbents respond with defensive Buy, Block, Pretend, and Link strategies.

Breakdown:

• Colony’s career spans six tech waves, from minicomputers to cloud, each disrupting incumbents. Gen/agentic AI now drives the 7th wave.

• Generative AI enables low-cost, adaptive software that threatens low-code/no-code platforms and legacy CRM/ERP systems.

• Colony outlines AI’s broader impact on hardware, tech services, and incumbent giants like Google, Meta, Amazon, Microsoft, and Apple.

• Incumbents deploy defensive strategies by buying challengers and blocking disruption through regulation, pricing, and partnerships.

• Other tactics include pretending to be part of the new era with rebrands and bundling AI into existing dominant products (e.g. Copilot in MS Office)

Why it’s important: Tech CEOs are scrambling to defend their market positions. Colony warns CIOs: beware of legacy vendors bearing AI gifts. Many are “faking it until they can make it.” If possible, delay major software changes until CRM/ERP offerings from AI-native vendors arrive in late 2026–2027.

OPPORTUNITY INSIGHT

McKinsey unpacks AI-quantum synergies

Brief: McKinsey’s latest Quantum Technology Monitor shows surging quantum computing (QC) investment and innovation could generate $1–$2T in value by 2035, unlocking powerful synergies for AI and other frontier technologies.

Breakdown:

• Quantum is a catalyst, accelerating progress across frontier technologies, from AI and robotics to cybersecurity and sustainability tech.

• Quantum algorithms could improve AI training efficiency by exploiting quantum advantages in linear algebra, search, and optimization.

• As AI models grow in size and complexity, GPU memory becomes limiting. Quantum hardware increases capacity and speeds up data loading.

• AI model training requires exponential compute, but classical hardware is plateauing. Quantum computing offers scalable computing power.

• AI could also accelerate quantum progress, advancing hardware discovery (e.g. superconductors) and optimizing error correction.

Why it’s important: Quantum may help resolve AI training constraints, while AI accelerates quantum development. NVIDIA, for example, is advancing this fusion with the launch of NVAQC in March 2025. Beyond AI, the approaching Q-Day, when quantum breaks encryption, demands urgent global readiness.

BEST PRACTICE INSIGHT & CASE STUDY

QuantumBlack shares MCP reuse progress

Brief: QuantumBlack, McKinsey's AI-focused capability, shared how its leveraging MCP, including integration into Brix, its proprietary gen AI asset marketplace, to enable seamless access and systematic reuse.

Breakdown:

• Brix lets teams publish MCP servers with tools, prompts, configs, and docs, creating reusable assets others can easily discover and reuse.

• QuantumBlack has 10+ MCPs in development, supporting 115+ reusable assets. MCPs now rival data pipelines/connectors as top assets on Brix.

• With 1,500+ staff across 40+ sites, reuse has been key to consistent and fast delivery of 15,000+ AI projects. MCPs now power the next S-curve.

• Brix is a mesh-compatible “AI Asset Registry” (see image above), built to deploy alongside broader agentic AI capabilities.

• Embedding Brix MCP into GitHub Copilot let engineers reuse assets from their IDE, reducing discovery time by 55%.

Why it’s important: AI presents vast opportunities and challenges, for instance, in interoperability, reusability, and scalability. Reusability goes beyond engineering best practices; it’s a key enabler of scale. With effective MCP reuse, enterprises can accelerate delivery and reduce maintenance overhead.

Andreessen Horowitz outlined how CFOs are navigating AI, from reinventing ARR to gross margin pressures, cost control, and ROI clarity.

Goldman Sachs forecasts that the software market, traditional SaaS and new AI agents, could grow an additional 20% to 45% by 2030.

AWS and BCG combined gen AI sales nudges and proprietary algorithms to improve AWS Partner outreach, driving a 65% regional sales pipeline uplift.

OpenAI is building a consulting arm charging enterprises $10M+ to customize models, placing it in competition with firms like Accenture and Palantir.

Google Cloud Consulting shared its Agentic AI Transformation Framework, an actionable roadmap for leaders to navigate the agentic landscape.

AWS’s Generative AI Index shows firms plan to prioritize AI spending over security in 2025, and Chief AI Officers (CAIOs) emerging as critical leaders.

Microsoft to cut a further 9,000 roles (~4% of staff), reducing managerial layers and increasing productivity with new technology.

Anthropic’s “Project Vend” had Claude run a company store for a month, revealing both promising management capabilities and business failures.

Anthropic is reportedly on pace to reach $4B in annual revenue, 4x higher than its projections at the beginning of 2025.

Cloudflare will now block AI crawlers by default on new sites and launched a marketplace where publishers can charge bots for content access.

OpenAI says it has no plans to use Google’s TPUs, countering reports that it would adopt rival chips to meet rising AI demand.

Meta continued its recruiting with four more OpenAI researchers, now eight in total, moving to Mark Zuckerberg’s new superintelligence unit.

Huawei open-sourced several of its Pangu models and underlying inference stack, trained using the company’s own Ascend chip infrastructure.

Cursor launched new mobile and browser apps that let users manage and monitor agents through natural language, outside the IDE.

Replit debuted Dynamic Intelligence, new features that enhance context awareness, reasoning, and autonomy for its agentic coding assistant.

Apple is reportedly considering leveraging AI from Anthropic and OpenAI for the revamped Siri over in-house models.

CAREER OPPORTUNITIES

J.P. Morgan - Head of AI Accelerator

Mastercard - AI Strategy Consulting Director

Databricks - AI Industry GTM Lead

EVENTS

Deloitte - Generative AI in Finance - July 29, 2025

AWS - Generative AI Summit - September 4, 2025

Gartner - Agentic AI in Enterprise - September 9, 2025

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