How to Use AI in Consulting Firms

We’re starting by conquering the spaghetti bowl of email threads! Nice to see Bloomberg feature the work we are doing to Rewire our firm and our client work with agents! #mckinseydigital #rewiredbook “At consulting firm McKinsey & Co., an AI agent now handles the tedium of client onboarding. It coordinates paperwork, shares relevant contact details, affirms the scope of the project — and runs everything by the firm’s legal, risk, finance, staffing and other departments to get their signoffs. “That used to be an absolute spaghetti bowl of email threads between all the different functions,” said Rodney Zemmel, who leads McKinsey’s digital practice and the firm’s own AI transformation. In the past, onboarding required tens of hours per new client. Now, “an agent basically does all that chasing for you,” and completes the process in roughly 30% of the time. It sends emails and follows up to wrangle whatever information it needs to move projects forward. The final product is then reviewed and approved by a human. “It works in this case because it's a complicated set of tasks, but actually a fairly standardized and routinized one, without too much judgment involved,” Zemmel said. Another application McKinsey is testing is a “squad” of agents to work together like a team of human employees would. McKinsey often helps companies migrate data from mainframes to the cloud — a “laborious, complicated, expensive process, ” Zemmel said. So McKinsey trained an agent squad to mimic the different team members that would typically staff the project, like designers and data engineers. While the squads are not yet fully operational, Zemmel said initial results have been impressive. “You can cut the time to do a mainframe to cloud migration more than in half by using these agent squads with the right degree of human supervision over the top, ” he said. Agents can be activated with natural-language instructions and are designed to be equally conversant with their human users. McKinsey recently gave access to an internal platform that lets everyone in the firm build their own agents. Allowing each employee to design the agents that would be most useful to them could bring major productivity benefits. But also, Zemmel said, “the potential to create absolute chaos is there,” so building the right safeguards around the agents is essential. At McKinsey, a central team will review all agents against cyber, risk, legal and data policies before they’re made available to the rest of the firm. Companies that adopt agents won’t replace entire departments overnight, Zemmel said. The new technology may even lead to a reversal of offshoring for functions like human resources, finance or tech. Instead of outsourcing work to a large team with an average skill set in a country with lower labor costs like India, companies get more out of employing a small but highly skilled team at home that’s leveraged by powerful agents.”

Step-by-Step Guide - Start in SAP AI space For Experienced SAP Consultants You’re an experienced SAP consultant. But now you want to break into SAP AI. Where do you start? This 6-step guide is your blueprint to enter one of the fastest-growing paths in enterprise tech. AI isn’t coming to SAP consulting. It’s already here - with Joule, AI Core, and the SAP Knowledge Graph leading the charge. If you’ve built your career in S/4HANA, MM, SD, or BW- You already have a huge advantage. You just need to bridge your SAP skills into the AI era. 𝗛𝗲𝗿𝗲’𝘀 𝘁𝗵𝗲 𝗲𝘅𝗮𝗰𝘁 𝗿𝗼𝗮𝗱𝗺𝗮𝗽 𝘁𝗼 𝗳𝗼𝗹𝗹𝗼𝘄: ✅ 𝗦𝘁𝗲𝗽 1 - 𝗟𝗲𝗮𝗿𝗻 𝗔𝗜 𝗙𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹𝘀 - ML, NLP, GenAI, Predictive Analytics - Study with SAP Learning AI Hub, OpenSAP, or Coursera ✅ 𝗦𝘁𝗲𝗽 2 - 𝗘𝘅𝗽𝗹𝗼𝗿𝗲 𝗦𝗔𝗣 𝗔𝗜 𝗧𝗼𝗼𝗹𝘀 - Get hands-on with Joule Studio, SAP Knowledge Graph, and AI Core ✅ 𝗦𝘁𝗲𝗽 3 - 𝗠𝗮𝗽 𝗨𝘀𝗲-𝗖𝗮𝘀𝗲𝘀 𝘁𝗼 𝗖𝗼𝗻𝘀𝘂𝗹𝘁𝗶𝗻𝗴 - Identify pain points in S/4 (Finance, Ariba, MM...) - Design automations around them ✅ 𝗦𝘁𝗲𝗽 4 - 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲 𝗼𝗻 𝗕𝗧𝗣 - Use AI Launchpad to deploy models and build intelligent agents ✅ 𝗦𝘁𝗲𝗽 5 - 𝗕𝘂𝗶𝗹𝗱 𝗥𝗲𝗮𝗹 𝗣𝗿𝗼𝗷𝗲𝗰𝘁𝘀 - Create RAG pipelines using HANA Cloud Vector Engine - Build Joule skills for end users ✅ 𝗦𝘁𝗲𝗽 6 - 𝗝𝗼𝗶𝗻 𝘁𝗵𝗲 𝗦𝗔𝗣 𝗔𝗜 𝗖𝗼𝗺𝗺𝘂𝗻𝗶𝘁𝘆 - 2M+ users, 430+ spaces, endless learning opportunities ➡️ 𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱: 𝗖𝗼𝗻𝘀𝘂𝗹𝘁 𝘄𝗶𝘁𝗵 𝗔𝗜 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝘆 - Use a bottom-up process mapping to assess AI readiness and prioritize use cases that deliver measurable ROI - Understand Agentic AI strategy: Joule’s sales and supply‑chain agents coordinate to automate multi‑step workflows—targeting real‑world use‑cases in 2025. ➡️ 𝗖𝗮𝗿𝗲𝗲𝗿 & 𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗚𝗿𝗼𝘄𝘁𝗵 - New roles emerging: AI‑enabled financial analyst, predictive maintenance consultant, AI procurement strategist, SAP AI specialist, automation implementation lead - Benefits for consulting firms: - Up to 14% faster project delivery using Joule consulting tools - Example: KPMG, Seidor reduce training time and speed discovery ✅ 𝗤𝘂𝗶𝗰𝗸‑𝗦𝘁𝗮𝗿𝘁 𝗖𝗵𝗲𝗰𝗸𝗹𝗶𝘀𝘁 [ ] Complete AI fundamentals training [ ] Finish "SAP Joule for Consultants" course from ZaranTech [ ] Join SAP Community AI discussions [ ] Prototype a Joule Agent using SAP BTP + AI Core + Build [ ] Publish a small AI‑in‑SAP proof‑of‑concept [ ] Upgrade consulting toolkit: decision support via Joule, predictive analytics dashboards [ ] Share insights to build thought leadership on LinkedIn, ZaranTech community You don’t need to start over. You just need to layer AI on top of your SAP domain knowledge. SAP consultants who learn AI in 2025 will define the projects of 2026. 𝗣.𝗦. 𝗪𝗵𝗶𝗰𝗵 𝘀𝘁𝗲𝗽 𝗮𝗿𝗲 𝘆𝗼𝘂 𝗼𝗻 𝗿𝗶𝗴𝗵𝘁 𝗻𝗼𝘄? 𝗗𝗿𝗼𝗽 𝗶𝘁 𝗶𝗻 𝘁𝗵𝗲 𝗰𝗼𝗺𝗺𝗲𝗻𝘁𝘀 𝗯𝗲𝗹𝗼𝘄 Save 💾 ➞ React 👍 ➞ Share ♻️ Follow Alok Kumar for SAP AI roadmaps you can actually follow.

Some of the best AI breakthroughs we’ve seen came from small, focused teams working hands-on, with structured inputs and the right prompting. Here’s how we help clients unlock AI value in days, not months: 1. Start with a small, cross-functional team (4–8 people) 1–2 subject matter experts (e.g., supply chain, claims, marketing ops) 1–2 technical leads (e.g., SWE, data scientist, architect) 1 facilitator to guide, capture, and translate ideas Optional: an AI strategist or business sponsor 2. Context before prompting - Capture SME and tech lead deep dives (recorded and transcribed) - Pull in recent internal reports, KPIs, dashboards, and documentation - Enrich with external context using Deep Research tools: Use OpenAI’s Deep Research (ChatGPT Pro) to scan for relevant AI use cases, competitor moves, innovation trends, and regulatory updates. Summarize into structured bullets that can prime your AI. This is context engineering: assembling high-signal input before prompting. 3. Prompt strategically, not just creatively Prompts that work well in this format: - “Based on this context [paste or refer to doc], generate 100 AI use cases tailored to [company/industry/problem].” - “Score each idea by ROI, implementation time, required team size, and impact breadth.” - “Cluster the ideas into strategic themes (e.g., cost savings, customer experience, risk reduction).” - “Give a 5-step execution plan for the top 5. What’s missing from these plans?” - “Now 10x the ambition: what would a moonshot version of each idea look like?” Bonus tip: Prompt like a strategist (not just a user) Start with a scrappy idea, then ask AI to structure it: - “Rewrite the following as a detailed, high-quality prompt with role, inputs, structure, and output format... I want ideas to improve our supplier onboarding process with AI. Prioritize fast wins.” AI returns something like: “You are an enterprise AI strategist. Based on our internal context [insert], generate 50 AI-driven improvements for supplier onboarding. Prioritize for speed to deploy, measurable ROI, and ease of integration. Present as a ranked table with 3-line summaries, scoring by [criteria].” Now tune that prompt; add industry nuances, internal systems, customer data, or constraints. 4. Real examples we’ve seen work: - Logistics: AI predicts port congestion and auto-adjusts shipping routes - Retail: Forecasting model helps merchandisers optimize promo mix by store cluster 5. Use tools built for context-aware prompting - Use Custom GPTs or Claude’s file-upload capability - Store transcripts and research in Notion, Airtable, or similar - Build lightweight RAG pipelines (if technical support is available) - Small teams. Deep context. Structured prompting. Fast outcomes. This layered technique has been tested by some of the best in the field, including a few sharp voices worth following, including Allie K. Miller!

Most of the AI business advice online is full of noise. I’ve spent the past year interacting with AI more than I did with real humans (RIP social life) and here’s how I think you can best leverage AI. The key to success? Have a strategy. If you want to lose weight, you can dive deep into the rabbit hole, try everything, then burnout. Or you can hire someone to give you a strategy: First count calories, then increase physical activity, then get enough sleep… etc. You don’t need diet pills or liposuction. Stacking small changes gradually is the only way to sustainable change. So here’s the prompts I’d use: *Replace text in [ ] You are a digital transformation and AI expert who helps [small and medium-sized commercial real estate developers and investors] streamline operations, save time, and scale impact. I want you to act as a trusted advisor to help me develop a focused AI strategy and implementation plan tailored to my business. Here is my goal: I want to identify the 20% of AI tools and workflows that will give me 80% of the impact, so I can build an efficient and integrated workflow using the latest practical technology - without creating bloat or needing a large engineering team. I prefer low-code or no-code solutions where possible. Start by asking me a series of thoughtful, structured questions to understand: - My business model and processes - My typical daily workflows - My existing tools and technology stack - My level of technical skill - My goals and pain points - Any constraints (budget, timeline, team size) Once you have enough information, propose a simple and actionable AI strategy, prioritized by impact and ease of implementation. Present this as a clear step-by-step plan I can follow, including tool recommendations where relevant.

𝗔𝗜 𝘄𝗼𝗻’𝘁 𝗸𝗶𝗹𝗹 𝗰𝗼𝗻𝘀𝘂𝗹𝘁𝗶𝗻𝗴. 𝗜𝘁 𝘄𝗶𝗹𝗹 𝗸𝗶𝗹𝗹 𝘁𝗵𝗲 𝗽𝗮𝗿𝘁𝘀 𝗰𝗹𝗶𝗲𝗻𝘁𝘀 𝗵𝗮𝘁𝗲 𝗽𝗮𝘆𝗶𝗻𝗴 𝗳𝗼𝗿. What gets automated fast (≈70–95% time saved): • Desk research & benchmarking: synthesize public + internal docs, cluster themes, draft citations. • Interview ops: auto-transcribe, tag, sentiment, pull quotes → instant “what we heard.” • Model stubs & forecasts: clean data, baselines, scenarios, sensitivities. • First-draft storylines & slides: pyramid outlines → branded decks; charts populated from data. • PMO busywork: status updates, RAID logs, risk heatmaps, next-step trackers. What gets augmented (≈30–70%): • Diagnostics & due diligence: automated checklists + anomaly detection; humans validate context. • Market sizing & pricing experiments: agent simulations create options; humans set constraints and priors. • Change assets: tailored comms, FAQs, training scripts; humans handle stakeholders. What remains stubbornly human (for now): • Problem framing and trade-offs (what not to do). • Politics, trust, and accountability with the exec team. • Ethics, risk appetite, and governance choices. • Judgment under ambiguity—deciding which signals matter. Net effect: fewer slide factories, more option architects. Pair AI with consultants to ship better lighthouses faster—and kill bad bets earlier. How consultants should adapt: 1. Lead with problem framing, not page count. 2. Productize AI-first workflows (research → analysis → synthesis → deck in hours). 3. Price outcomes and options, not days. 4. Build client RAGs on their own corpus (privacy-first). 5. Treat AI as a portfolio: annuities (automation), growth stocks (scale what works), options (cheap experiments). AI will replace a chunk of work. It will not replace ownership. That’s why the best consultants, those who bring judgment, speed, and skin in the game, will matter even more. It won’t absorb blame. Consultants will still be around in 2030 because organizations buy more than deliverables: judgment, speed, and—yes—a buffer for risk and accountability. Harsh? Maybe. True? Often. What else keeps consulting durable?

After talking with Robbie Bent last week, I’m convinced every digital worker should hire a personal AI consultant. I know I will. The irony? Robbie’s company, Othership, is an antidote to tech—a social bathhouse where phones are banned to encourage presence and human connection. Yet, he’s deeply focused on technology and how it can improve the way he runs his business. After hours of hearing about AI’s potential in tech podcasts, Robbie wanted to move beyond ChatGPT and integrate AI into his workflows. He realised trying out all the latest tools himself was going to be a full-time job, and that’s when he decided to hire a personal AI consultant—someone who could analyze his processes and identify how AI could drive real efficiency gains. The goal was to eliminate busywork and free up his time for higher level decision-making. Think Accenture, but for the entrepreneurial age. He had four criteria for the person he wanted to work with: 🏗️ Strong engineering background  🥷 Startup experience  🎖️ 10-12 existing clients who had already implemented successful AI solutions  💰 High consulting rates ($500-$1,000/h) to signal expertise and focus on ROI They started by spending an hour reviewing Robbie’s workflow and focused on the highest leverage areas, including recruiting & hiring automation, sales & outreach and negotiation coaching. One interesting industry-specific use case they came up with was to train a model on all the construction-related meetings and documents to have it extract key takeaways, flag issues and track progress, eventually helping them minimize risk in their expansion, a critical challenge for brick & mortar businesses. The consultant then went in implementation mode, testing AI integrations in real time. This typically involved stitching together different AI models, workflow automations, and tools. Robbie didn’t stop at his own workflow. He decided to give all his senior leaders access to this personal AI consultant, so they too could optimize their own processes. The goal is to make AI a core part of how everyone in the company operates. It’s not a “once and done” type of project. AI capabilities are growing so fast, that what isn’t possible today may become possible in six months. Robbie plans to repeat this process annually, ensuring his company is always operating at the cutting-edge. His key takeaways from his first-hand experience so far: 1️⃣ AI is not replacing jobs per se but multiplying the effectiveness of great employees 2️⃣ While brick-and-mortar locations won’t see major AI-driven changes, corporate HQ roles could be optimized, potentially reducing the need for middle management 3️⃣ AI tools aren’t fully automated yet 4️⃣ Employees need AI training: how to integrate AI into daily workflows, what data to input for optimal results, when to trust vs. refine AI-generated content, etc. Drop a comment if you’d like me to share details on the AI consultant he’s been working with!

Enjoy the 4th of July and take a moment to reflect on how you can incorporate AI into your business. Here’s what we did. We built an AI platform to help our managers be more effective in less time. How we started: Instead of just looking at mundane tasks, we thought the intersection of time and output value to be the right place to start. So, we reviewed all their tasks and outlined which took the longest but provided them the greatest value in helping them effectively coach, manage, and report on their team. From there an obvious place to start emerged. So we got to work on building the AI model and platform that we immediately put into action and testing with a small group. From there with the feedback we iterated over and over to ensure the AI was doing what we needed it to do, while at the same time making the platform as straightforward to use as possible. Once it worked and we were comfortable, we rolled it out to the entire team. Of course, this process then requires a change management project, which is just as much work and I will talk about in a different post. What you could do: I would start with looking at your managers as any productivity gains you find in this group will have an exponential gain for the organization given their: - high impact decision making, and -the potential cascading effects (ie if managers adopt AI it is more likely your other employees will adopt AI in future initiatives) Then I would interview your managers to understand what tasks in their week take the longest to complete but provide the greatest value. Have them rank tasks from most to least useful to help their team effectiveness. The top of the list is likely where you should start looking to incorporate AI. From there you will need some product, technical, and development resources to plan and execute on the project. Let me know if this part is a hang up for you! Want to spitball ideas for your business? DM me! #AI #entrepreneurship #scaleup

AI integration isn’t a tech problem. It’s a workflow problem. After helping over 20 USA-based mid-sized companies adopt AI, we’ve seen the same thing again and again. They don’t need GPT-5. They need clarity. Here’s the 3-part framework that works: 1. Unify your team. Centralize AI usage with Copilot, Gemini, or CollabAI 2. Train with structure. Use job-specific demos, agents, and cheat sheets 3. Deploy fast. Launch one agent. Track ROI within 30 to 60 days This is already working in the field: → An accounting firm gained back 20 hours a week. 10 AI agents now reply to client emails, handle newsletters, and manage marketing tasks so their team can focus on actual accounting work. → A nonprofit is spending more time in the field. Agents review documents 5x faster, draft social media posts, and write donor letters in their tone with one click. → A law firm’s AI assistant handles research, flags key case points, and drafts admin tasks freeing up legal staff for real client work. AI agents don’t need to be perfect. They just need to work. If your team is still stuck in “exploring AI,” it’s time to move into execution. Comment Agent Ready or DM me to see how mid-sized USA companies are scaling smart with agents that get things done. What’s one task in your business that should already be automated? Let’s compare notes. Notes : images below generated using ChatGPT new version and one using flux ai ! Identify which one flux

"So You Want To Be An AI Consultant?" Episode 1: The Sales Team Value Proposition Arshad Imran reached out to me a few weeks ago asking about what it takes to become an AI consultant. We have had several discussions with the last one getting into the details. His questions were insightful and I plan to share many excerpts to help other people understand why they would hire an AI consultant or how they need to think if they want to become one. I am not a coder and do not have a background in data science. To succeed in this field, you need to be able to understand specific use cases and tools that can help. Breaking down the real ROI of AI consulting through a practical sales team example: The Problem: ▶️ Sales reps spending 3+ hours per prospect on research and documentation ▶️ Limited preparation time between meetings ▶️ Valuable selling time lost to administrative tasks The AI Solution: ▶️ Cut prospect research from 1 hour to 5 minutes using Perplexity, Humantic, and Claude ▶️ Reduce post-call documentation from hours to minutes ▶️ Enable quick meeting prep and prospect communication even between back-to-back calls The Business Impact: ▶️ 20% efficiency gain per sales rep ▶️ For a 10-person team at $100k base salary each ▶️ Annual efficiency value: $200,000 Result: More time selling, less time on bureaucracy Key Takeaway: AI consulting isn't about fancy tech - it's about solving real business problems with measurable results. What aspects would you like me to cover in future episodes?

Everyone is talking about AI, but too many companies are focused on its lower-value applications. The real power of generative AI isn't in automating daily tasks; it's in its ability to function as a high-level research and consulting assistant. Our firm leverages this for our clients in two critical ways: ·       Strategic Research: AI can be an incredibly fast and efficient research partner, helping to sift through vast amounts of data to find key insights that inform major business decisions. ·       Ideation & Brainstorming: It's a strategic sparring partner, helping to generate and refine new ideas for growth, market entry, or operational improvements. These are lower-frequency, high-value tasks that move the needle. Stop using AI for quick fixes and start using it as the strategic partner it was built to be. #GenerativeAI #StrategicPlanning #BusinessResearch #AIAdoption #Consulting