Tech Innovations Reshaping the Consulting Landscape

➡️ KPMG journey to build an agentic tax advisory system is a benchmark for technical transformation in consulting. After rigorous risk analysis (including securing sensitive PII), they moved all tax advisory knowledge often scattered across partners’ laptops and documents into a centralized, retrieval-augmented generation (RAG) architecture. Their platform (KPMG Workbench) uses a federated approach, integrating multiple LLMs (OpenAI, Microsoft, Google, Anthropic, Meta) for future-proof model flexibility. To construct “TaxBot,” KPMG’s team engineered an extensive 100-page instruction prompt, refined over months. This prompt defines operational context, intake structure, workflow, compliance guidance, and directs interaction between human experts and the agent. TaxBot ingests four to five key client parameters, then prompts iterative expert input before auto-generating a robust 25-page draft, synthesizing internal tax advice and Australia’s entire tax code. The agent sits behind strict access controls (usable only by accredited tax professionals), maximizing safety and accuracy. 👉🏼 It slashed advisory delivery from two weeks to one day. KPMG’s technical leadership also built agent runtime services, enabling multi-agent workflows writers, editors, and credential managers collaborate in an asynchronous framework to automate document production and knowledge management. Their story is not just about speed, but how a technical prompt engineering discipline, retrieval-augmented architectures, and federated LLM selection can reshape high-impact professional services for resilient innovation. If you’re thinking about agentic automation in highly regulated domains, KPMG’s approach deep prompt engineering, multi-model orchestration, RAG, human-in-the-loop should be your blueprint. #genai #ai #RAG #LLM #KPMG

Stop calling yourself a “consulting firm.” That title is going extinct. We are also changing it :O If you’re still selling decks, manual analysis, and time-based retainers... You’re building a 2010s business in a 2030s world. Let me break this down based on what we’re seeing right now: Top firms are already shifting: BCG is piloting internal agent ecosystems for research + benchmarking McKinsey is training junior consultants to become prompt engineers Deloitte is building LLM-based decision simulators for client strategy They’re not replacing consultants. They’re augmenting them — turning smart people into insight orchestrators. The new consulting model looks like this: 1. Agent-powered discovery Research, insight summaries, opportunity analysis Tools: Perplexity AI, ChatGPT 2. Prompt-native consultants Deep domain expertise + ability to guide LLMs Trained on frameworks, not just templates 3. Simulated decision-making Predictive agents stress-test strategy recommendations Open-source projects like AutoSimulate are just the start 4. Productized service layers Playbooks turn into micro-platforms Deliverables evolve into dashboards, agents, automations Real example from our world: We helped a boutique consultancy deploy HR AI to: ✅ Analyze 5 years of hiring and retention data ✅ Build a talent intelligence dashboard ✅ Simulate the impact of hybrid policy shifts Result? - 40% drop in attrition - New $400K+ recurring revenue stream from productized delivery The uncomfortable truth? - Insight alone won’t be enough. - It’s insight orchestration that will win. Don’t fight the AI shift — build on it. You’re not just a consultant anymore. You’re a strategist, a systems thinker, and a conductor of agents. And the firms who lean in? They’re not going extinct. They’re becoming the platforms of the next decade. #AgenticAI #Consulting #LLMs #FutureOfWork #AIConsulting #LiquidTechnologies #Strategy

We surveyed ~100 mid-market consulting firms to see how they were using - or not using - AI in their work. Tried my best not to pass judgment, but the results were WILD. Here were the 5 most surprising insights: 1️⃣ 90% are using LLMs, but 10% banned them outright. No surprise that ChatGPT is the go-to tool for client work. What was surprising: a small but vocal minority BANNED LLMs completely. Their rationale? If AI could generate research or analysis, it risked eroding the “secret sauce” - aka, the expertise consultants pride themselves on selling. 2️⃣ Many firms use AI, but hide it from clients. A striking number of consultants AND leaders admitted they quietly use AI behind the scenes, but never disclose it. The worry is that clients would see it as “cheating” or assume they’re getting less value. Ironically, clients usually just want faster insights and better outputs; they don’t care how the sausage gets made. 🤷♂️ 3️⃣ Existential fear of the business model. Roughly two-thirds of leaders told us their biggest anxiety wasn’t about the tools themselves, but what they mean for consulting as an industry. If AI can deliver faster and cheaper, what happens to premium fees and the billable hour? 4️⃣ The consulting pyramid is starting to crack. Several leaders admitted they’re already questioning the need for analyst classes. If AI can take the first pass at research, analysis, and drafting, the traditional “leverage model” - a wide base of junior consultants feeding a narrow partner tier - doesn’t make as much sense. The pyramid may be flattening faster than anyone expected - or maybe it's turning into a diamond? 🤔 5️⃣ Pilots are common, but scaling is rare. Nearly 9 in 10 firms had tested AI for tasks like drafting deliverables, automating parts of analysis/research, or knowledge base management. But fewer than 1 in 5 had a roadmap or governance model for rolling it out firmwide. Leaders see the upside; but without structure, they stay stuck in experimentation mode. The big takeaway? AI is everywhere in consulting - but firms are split between cautious experimentation, quiet adoption, and existential questions about what comes next. 👉 These findings surprised me: which one do you think will have the biggest impact on boutique and mid-market consulting firms? #Consulting #MBB #AI #AIConsulting #Big4

Reflecting on My First Strategy-Consulting Startup - And How I’d Build It in 2025 When we founded Scientia Advisors back in the late 2000's, the “tech stack” was PowerPoint, spreadsheets, and enough coffee to keep a small city awake. Fast-forward: Accenture just poured $3 billion into GenAI, McKinsey & Company’s QuantumBlack pipeline is bursting, and the Big Four are re-tooling entire practices around large-language models (LLMs). If I were launching today, I’d design an AI-native consultancy from day one. Here’s the playbook I’d follow - and why it matters for every organization, not just consultants: Deep Research at Hyperspeed LLMs compress weeks of document dives into hours of synthesis. Humans still own the so-what? - stress-testing insights against messy reality. Persona-Driven Insight Generative AI can create lifelike personas - front-line operators, skeptical CFOs, even regulators - so we can pressure-test strategies before they hit the wild. Think digital ethnography, minus the clipboards. Industry Nuance on Demand Domain-tuned models surface industry economics or pharma compliance in seconds. Seasoned experts can then translate those nuances into action - and spot the cultural landmines a model can’t. Why This Matters Beyond Consulting Whether you sell sneakers, satellites, diagnostic products, therapeutics or surgical robots, your strategic moat widens - or shrinks - based on how accurately you read AI’s trajectory. Waiting for certainty is a choice, with compounding opportunity cost. The Human Dividend As raw analysis races toward zero, the premium shifts to: C-suite empathy & trust-building Cross-industry pattern matching (a.k.a. scar-tissue advantage) Ethical guardrails & risk arbitration AI isn’t replacing deep experience; it’s reshaping the value curve. Firms - and leaders - that fuse silicon speed with human judgment will own the next decade. IMHO - The time is now to rethink your strategy in this AI-accelerated/augmented world. #AI #Consulting #McKinsey #Accenture #DigitalTransformation #DeepResearch #Personas #FutureOfWork Arshad Ahmed