Consultants: Claude Now Builds Client Decks Right in Chat

An ex-McKinsey consultant spent a weekend testing five AI presentation tools against the exact bar he learned during his years at the firm — the same 20-page business-case brief, run through each one. His conclusion, published just a few weeks before Anthropic’s latest launch: “None of the five tools tested produces a deck I would send to a client today.” That verdict is worth keeping in your back pocket, because on September 16, 2026, Anthropic gave every Claude Pro and Max subscriber a new tool — Claude Slides, built directly into the chat you already use — and the first wave of takes online are already calling it “a PowerPoint magic wand.” Both things are true at once, and the gap between them is exactly what this post is about.

What Just Launched, and Why Consultants Specifically Should Care

Anthropic merged its Claude Cowork and Claude chat products into one unified experience on Tuesday, and bundled in two new tools: Claude Docs and Claude Slides. You no longer need a separate add-in, a different tab, or a code-execution toggle to get Claude to build you a presentation. You just ask, in your normal conversation — “turn this analysis into a 12-slide client deck” — and an editable deck appears in the chat. Edit individual slides, present straight from Claude, or download the whole thing as PowerPoint or PDF.

Source: Slideworks

Source: Axios

If you’ve spent any time in strategy or management consulting, you already know why this lands differently for your profession than it does for a general office worker. The client deck isn’t a nice-to-have output of your work — for a huge chunk of the industry, it is the deliverable. The analysis matters, obviously. But the thing that gets FedEx’d (or emailed, these days) to the client, presented in the boardroom, and referenced for the next eighteen months is the deck. Anything that touches deck-production time touches the most expensive hours in the business.

That’s exactly why r/consulting lit up almost immediately with people calling this “a PowerPoint magic wand” — and it’s also exactly why the honest answer here is more complicated than the hype. Let’s get into the actual research on what AI-drafted decks look like once someone who’s built hundreds of consulting decks looks closely.

It’s also worth being clear about what’s actually new here versus what’s just newly convenient. Consultants have been feeding notes into ChatGPT and Claude to get slide help for well over a year at this point — nothing about “use AI to help build a deck” is a September 2026 invention. What changed on Tuesday is the friction. Before this week, getting an actual editable, downloadable deck out of Claude meant a separate add-in, a different tool, or a code-execution workaround that most people never bothered figuring out. Now it’s the same chat window you already have open, with zero extra setup. That’s a meaningfully lower bar to clear, which is exactly why the volume of people trying this for the first time has spiked — and why it’s worth being precise about what it can and can’t do before that first wave of new users sends something half-finished to a client.

The Reality Check, From Someone Who’s Actually Tested This

The most rigorous public test of AI presentation tools against a genuine consulting bar comes from Mats Stigzelius, a former McKinsey consultant writing for Slideworks, published May 29, 2026. He ran the same roughly 20-page software-implementation business case through five different tools — Perceptis, Decky AI, Deckary, Claude Design (the older, separate tool — not the new native Slides), and Slidely — judging each on storyline quality, close-up slide quality, PowerPoint export, and total time spent.

His conclusion was blunt: “No AI tool yet generates slides ready to send to a client without significant editing.” Even the two strongest performers in his test — Perceptis and Decky AI — looked genuinely consulting-grade at first glance, but close inspection revealed the tells: inconsistent spacing, mismatched font sizes across slides, hardcoded colors that didn’t adapt to the client’s actual slide master, and in some cases outright hallucinated content sitting inside an otherwise clean-looking layout.

Here’s the detail that should reframe how you think about using any of these tools, Claude included: Stigzelius found that fully AI-drafted slide content often created negative productivity. His words: “The fully hallucinated slides are — surprisingly — not helpful at all. They take more time to fix than building the slide from scratch would take.” His actual recommendation was to use AI for “storyline scaffolding and inspiration only” — keep the structure and the section headers, then discard the generated body content and rebuild it against your real project evidence.

That test predates the native Claude Slides feature by almost four months, and it’s worth being precise about what that means. It doesn’t tell you Claude Slides specifically will produce the exact same failure pattern — Anthropic’s new native tool is a different product than the older Claude Design tool tested there. But it tells you something more useful: it establishes the actual bar every AI presentation tool has to clear, and as of this week, nobody has published an equivalent hands-on test of the brand-new native Claude Slides against that same bar. Until someone does, the responsible assumption is that Claude Slides inherits the same category-wide weaknesses — hardcoded styling, imperfect master-template fidelity, and content that needs a human “last mile” — until proven otherwise.

Here’s the tool-by-tool breakdown from that review, which is worth studying even though it predates Claude’s native Slides — it’s the clearest public map of exactly where AI presentation tools fail a real consulting bar:

A separate nine-tool test from Oria, published in July 2026, tested a dense operating-model slide with a KPI callout — closer to the kind of exhibit an actual engagement deck contains — and found a consistent pattern: tools built for clean, standard narratives (Gamma, Pitch, Canva, Beautiful.ai) performed well on simple slides but struggled with strict template conformance and dense, bespoke structure. That’s the same weak spot showing up across a completely different set of tools, which is exactly why it’s the section of this post you should trust the most.

The 5-Step Workflow That Actually Works

Based on how the strongest consulting-facing tools and reviews describe a defensible process — and how actual consulting firms are already using their own internal AI tools — here’s the workflow that gets you real time savings without the credibility risk of sending an obviously AI-made deck to a client.

Step 1: Start from your actual evidence, never a blank prompt. Paste in your real research pack — interview notes, the data model, prior deliverables, whatever the case team has already built. The Slideworks review is specific about why this matters: fully invented body content took longer to fix than writing from scratch. Give Claude something real to work from, and you dramatically cut the hallucination risk.

Step 2: Get the storyline before you get the slides. Ask Claude for a page-by-page storyboard — just titles, no full slide content yet — before you let it generate 20 or 40 finished pages. This is the single highest-leverage move in the whole workflow. Editing a ten-line storyline takes minutes. Editing forty completed slides after the fact does not. Rewrite every title into an actual conclusion (an “action title,” in consulting terms) before moving forward — “Q3 Revenue Declined 12%” beats “Q3 Revenue Overview” every time, and this is exactly the kind of instruction Claude needs explicitly, not implicitly.

Step 3: Generate inside your actual template, not a generic theme. If you have a real client template or house style deck, describe it explicitly or upload a sample slide and ask Claude to match its fonts, colors, and layout patterns. This won’t guarantee perfect brand fidelity — no tool on the market has fully solved this yet — but it meaningfully narrows the gap between “generic AI deck” and something closer to your firm’s actual look.

Step 4: Rebuild the dense, high-stakes exhibits by hand. This is the part every review agrees on: AI tools are strong at clean, single-message slides, and consistently weaker on dense operating-model diagrams, multi-column data tables, and bespoke exhibits with KPI callouts. If a slide is going to be the one the client stares at for five minutes, build or rebuild that one manually — even if you let Claude draft everything else.

Step 5: Run an actual quality pass before it leaves the building. Check spacing, font consistency, chart accuracy against your real numbers, and add whatever your engagement requires — source footers, exhibit numbers, definitions, an owner-and-date next-steps slide. Treat this exactly like the final review any junior analyst’s deck would get from a manager before a client sees it. The tool doesn’t get a pass that a human wouldn’t.

A worked example. Say you’re two weeks into an operating-model engagement and need a mid-point readout deck for the steering committee. You’d paste in your interview summaries and the current-state process map, then ask Claude for an eight-slide storyline: “Current State Findings,” “Three Root Causes of Delay,” then one slide per cause, then “Recommended Operating Model,” then “90-Day Implementation Plan.” Review just those eight titles — reject or reorder before a single full slide gets built. Once the storyline’s approved, let Claude draft the supporting content for the three straightforward findings slides, but plan to rebuild the operating-model diagram and the implementation timeline yourself — those are exactly the dense, structurally bespoke slides every review flags as the weak point. Total time saved: probably an hour or two on a deck that would’ve taken half a day. Total time saved on the two hardest slides: close to zero, and that’s fine — that’s not what the tool is for yet.

What This Looks Like at Real Firms

It’s worth knowing that the firms setting the bar for “consulting-grade” already have their own answer to this, and it’s instructive. McKinsey’s internal generative AI platform, Lilli, has answered nearly 19 million prompts since its 2023 launch, and the firm reports engagement teams save 4–6 hours a week specifically on presentations and research combined. BCG built an internal tool called Deckster — a slide editor trained on 800–900 of the firm’s own templates, with a “review this” feature that grades slides against manager-level standards — and roughly 40% of associates use it weekly. Bain’s internal tool, Sage, does something similar, and the firm says gen-AI-powered tools touched more than a quarter of its work as of late 2024.

Notice what none of those firms claim: that their internal tool autonomously produces a final, client-ready deck with no human involvement. Every one of them is described as an assistant inside a workflow that still ends with a human review. That’s the same posture this post is recommending for Claude Slides — not because Claude is uniquely limited, but because that’s genuinely how the best-resourced firms in the industry, with far more engineering investment than a solo practitioner has, have chosen to deploy AI in this exact function.

One more governance detail worth flagging if you’re at a firm with client confidentiality obligations: McKinsey staff have told reporters that consultants can use general tools like ChatGPT with guardrails, but cannot enter actual client data into them. If your firm has a similar policy — and most do — check whether Claude Slides falls inside or outside that boundary before you paste in anything client-identifiable. This is a compliance question, not a product question, and it’s on you to check it with your firm’s actual policy, not assume the answer.

What This Means for You

If you’re a solo or boutique consultant without an internal AI tool — this is genuinely useful, with real limits. You don’t have McKinsey’s engineering budget to build a custom Deckster, so Claude Slides is likely your closest equivalent. Use the five-step workflow above religiously, especially the storyline-first step, and budget real time for the manual polish pass. Don’t skip it because you’re solo and there’s no manager to catch it.

If you’re a first- or second-year analyst — this changes what “grunt work” looks like, but it doesn’t remove your job. The formatting and first-draft-generation work AI now handles was never the valuable part of your role anyway; the judgment about what the data actually means was. Use the time this saves to spend more hours on the analysis, not fewer hours total.

If you’re a manager or engagement lead reviewing a team’s decks — assume AI involvement is happening whether it’s disclosed or not, and adjust your review accordingly. Look specifically for the tells the Slideworks review flagged: inconsistent spacing, generic chart styling, or a storyline that reads clean but doesn’t quite match the underlying evidence. Those are the seams AI-assisted work leaves behind right now.

If you’re pitching new business, not delivering an engagement — the calculus is a little different. A pitch deck built fast with Claude, then polished, can help you compete on responsiveness against firms that take a week to turn around a proposal. Just don’t let speed become a reason to skip the fact-check pass — a wrong number in a pitch deck costs you the credibility a fast turnaround was supposed to buy you.

If you’re at a firm with strict client-data policies — resolve the compliance question before you resolve the workflow question. Check with whoever owns your firm’s AI usage policy about whether client-identifiable information can go into Claude Slides at all, the same way you’d check before using any new tool with sensitive data.

If you’re already paying for Gamma, Perceptis, or another dedicated deck tool — Claude Slides probably doesn’t replace that subscription yet, especially if you’ve already built templates or workflows around one of those tools. Think of Claude Slides as a strong option if you’re starting from zero, not necessarily a reason to switch if you’ve already got something working.

If you’re a fractional or interim executive building your own decks — you’re likely doing this work without a support team, which makes the time savings here more meaningful than for someone with an analyst to hand formatting to. Lean into Step 2 especially — approving the storyline before generating full slides — since you won’t have a second set of eyes catching a wrong turn early.

If you train or onboard new analysts — this is worth building into how you teach deck construction from day one. Rather than banning AI tools outright or pretending they don’t exist, teach the five-step workflow explicitly, including exactly where the tool needs a human check. New analysts who learn “AI drafts, I finish” as a habit from the start will produce more reliable work than ones who either avoid AI entirely or trust it blindly.

Edge Cases and Troubleshooting

“My consulting friends were annoyed when they realized my deck was AI-made.” This actually happened to someone publicly this week — a founder posted that her consulting friends were “furious” after spotting an AI-made deck, even though the content itself was solid. The tell is almost always visual, not substantive: a specific font pairing, particular spacing patterns, or a generic chart style. The fix isn’t to hide that you used AI — it’s to do the manual polish pass thoroughly enough that the tells disappear.

“Someone on my team said they wouldn’t even open a deck sent as a Claude Slides link.” This reaction is real and you should plan around it, not argue with it. Some clients and colleagues have a strong preference for receiving an actual file rather than a link to a hosted tool. When in doubt, export to PowerPoint or PDF and send the file itself rather than a Claude Slides link, especially for external-facing work.

“The chart Claude generated doesn’t match our source data exactly.” Verify every number before it goes to a client — this isn’t optional, and it’s not a Claude-specific step. No AI tool independently checks your data for accuracy; it builds a visual around whatever you feed it. Treat AI-generated charts exactly like you’d treat a first-year analyst’s first draft — checked against the source before it ships.

“The deck felt genuinely fast to build but Claude clearly reused a generic layout for our dense operating model slide.” This matches the exact failure pattern independent testing found — dense, multi-element slides with KPI callouts or nested structure tend to get simplified into a generic layout rather than handled with full fidelity. Plan on rebuilding that specific slide type by hand rather than fighting the tool to force it.

“I’m not sure if I’m allowed to put client data into this.” Stop and check your firm’s AI usage policy before proceeding, not after. This is genuinely one of the more common ways consultants get into trouble with new tools — assuming a policy that covers “AI tools generally” automatically covers a brand-new feature that launched three days ago.

“My deck looks great until I open the PowerPoint export.” Export fidelity — specifically whether text boxes and charts stay fully editable versus getting flattened into static images — hasn’t been independently and rigorously tested yet for this exact new feature. Open every export in actual PowerPoint before you rely on it, especially anything with charts, and budget time for a cleanup pass if elements come through as flattened images.

“A partner asked how I built the deck so fast, and I wasn’t sure how to answer.” This is becoming a real workplace moment as these tools spread faster than firm norms around them. The safest answer is the honest one: you used AI to draft the structure and first-pass content, then did a manual review and rebuild on the dense exhibits — which, per every review referenced in this post, is exactly the responsible way to use these tools right now. There’s no reason to hide a workflow that matches industry best practice.

“I don’t have time to run all five steps on every deck.” Fair — not every deck justifies the full workflow. Scale it to the stakes: an internal weekly update probably only needs steps 1, 2, and 5. A client-facing deliverable or board presentation should get all five, especially the storyline-review step, because that’s where a bad first instinct compounds across dozens of slides instead of getting caught early.

What This Can’t Do (Yet)

It cannot independently produce a client-ready deck with no human review. Every piece of evidence available right now — the most rigorous public consultant-run test, plus how the top three firms use their own far more sophisticated internal tools — points to the same conclusion: AI drafts, humans finish. Anyone selling you a “fully autonomous client deck” pitch is ahead of what the evidence supports.

It doesn’t verify your data or your logic. If your storyline has a gap or your numbers don’t tie out, Claude will build clean-looking slides around whichever version you gave it. The analytical rigor is still entirely yours.

It won’t match your firm’s exact template out of the box. Custom fonts, exact color codes, precise logo placement — all of this requires deliberate instruction, and even then, expect the tool to get close rather than exact.

It can’t handle dense, bespoke exhibits as well as clean single-message slides. Multi-column data tables, nested operating-model diagrams, and anything with more than a handful of interacting elements are the documented weak point across every AI presentation tool tested so far, Claude included.

It doesn’t resolve your firm’s client-data policy for you. Whether client-identifiable information is allowed inside this specific tool is a compliance question you need to answer with your own firm, not something the product itself decides for you.

It can’t replicate a firm’s exhibit numbering, footer, and source-citation conventions automatically. These are exactly the kind of small, engagement-specific formatting rules — sourced footers on every data slide, a consistent exhibit ID scheme, standardized definitions — that separate a genuinely audit-ready consulting deck from a merely nice-looking one. Every review referenced in this post treats these as a manual final step, not something current AI tools apply on their own.

It doesn’t know your firm’s unwritten style rules. Every consulting firm has house conventions that never got written down anywhere Claude could learn them — how aggressive the action titles should read, how much white space a partner expects, whether charts get labeled a specific way. That tacit knowledge still lives entirely with your team, and no AI tool available today has a way to absorb it without you spelling it out explicitly, prompt by prompt.

Frequently Asked Questions

Is Claude Slides good enough for client-ready decks yet? Not without human review. The most rigorous public test of AI presentation tools against a genuine consulting bar concluded that no tool tested produces a deck ready to send to a client without significant editing — and that test predates this exact launch. Treat Claude Slides as a strong first-draft tool, not a finished-deliverable machine.

How is this different from Claude Design, the older tool? Claude Design was a separate tool you had to navigate to outside your normal chat. Claude Slides is built directly into the conversation you’re already having — no add-in, no separate tab — and specifically optimized for presentation-shaped output rather than general visual design.

What’s the single biggest mistake consultants will make with this tool? Skipping the storyline-review step and letting Claude generate a full deck straight from a vague prompt. Reviewing and rewriting the titles before any slide content gets built saves far more time than editing a finished deck after the fact.

Can I use this for a pitch to a prospective client? Yes, with the same caveats as any client-facing use — treat the first draft as a starting point, verify every number, and do a manual polish pass before it goes out. Speed is a real advantage here, but not at the cost of accuracy.

Do McKinsey, Bain, and BCG use tools like this? They use their own internal versions — McKinsey’s Lilli, BCG’s Deckster, and Bain’s Sage — all of which function as assistants inside a workflow that still ends in human review, not as autonomous deck generators. That’s the model worth following even if you don’t have access to a custom internal tool.

Is it safe to put client information into Claude Slides? That depends entirely on your firm’s specific AI usage policy, which you should check before assuming. Many firms allow general AI tool use with guardrails but explicitly prohibit entering client-identifiable data — verify this with whoever owns AI policy at your firm rather than guessing.

Will this replace junior analyst deck-formatting work? It changes the nature of that work rather than eliminating the role. The formatting and first-draft generation get faster; the judgment about what the analysis actually means, and the manual work on dense or high-stakes exhibits, still needs a person.

How long does the manual polish pass typically take? Based on the available reviews, expect meaningful time on anything client-facing — reviewers described going from a “70% there” AI draft to something client-ready as substantial remaining work, not a five-minute touch-up. Budget accordingly rather than assuming the tool gets you all the way there.

Should I tell my client I used AI to build part of the deck? There’s no universal industry standard on disclosure yet, and firm policies vary. What matters more practically: the deck needs to hold up to scrutiny regardless of how it was built, so focus your energy on the quality-control pass rather than the disclosure question — a well-reviewed AI-assisted deck and a well-built manual one should be indistinguishable to the client either way.

Is this worth using for internal-only decks, like a steering committee update? Yes, probably more than for client-facing work. Internal audiences are generally more forgiving of minor visual inconsistencies than a paying client, which makes internal readouts, team updates, and steering committee decks the lowest-risk place to start building comfort with the tool before using it on anything external.

The Bottom Line

The honest read on Claude Slides for consulting work is neither “this changes everything” nor “this is a toy.” It’s a genuinely useful first-draft tool that saves real time on the parts of deck-building that were never where your value lived anyway — and it comes with the exact same human “last mile” that every AI presentation tool on the market still requires, according to every rigorous test published so far. Use the five-step workflow, keep your firm’s data policy in mind, and don’t let a client see anything you haven’t personally reviewed.

If you want to go deeper on using AI as an actual consulting practice — not just for slides, but for research, client communication, and the broader toolkit — our AI for Consulting & Advisory course covers the full picture, free to start.

Sources

• Anthropic — Claude Cowork and chat are now one Claude
• Slideworks — Best AI Presentation Tools for PowerPoint: An Ex-McKinsey Consultant’s 5-Tool Experiment & Review
• Oria — Best AI Presentation Tool for Strategy Consultants: 9 Tested
• SlideSpeak — How to Make a McKinsey-Style Presentation with AI
• 2Slides — Are AI-Generated Presentations Good Enough for Business? An Honest Assessment
• McKinsey — Meet Lilli, our generative AI tool: a researcher, time saver
• Business Insider — How AI Is Transforming Consulting at McKinsey, BCG, and Beyond
• Business Insider — Inside BCG’s AI product assembly line
• Bain & Company — AI-powered tools across its practices
• Live X/Twitter reactions, September 16, 2026: consultant and community reactions to the Claude Slides launch, including credibility and export-fidelity concerns