Specialized AI slide generator or general AI model? Which method is best for consulting slides?

Back in May, we tested five different AI tools for generating consulting-level slides. Our results then showed the none of the tools came close to real consulting deliverables, but specialized, consulting-focused tools were generally better.

Since then, the large AI labs in the forms of OpenAI and Anthropic have taken big steps forward in slide generation. We were therefore excited to re-do our test from May and see what the changes are.

In this article, we cover the three overall types of AI slide tools available today (October 2026), how we tested six of them on the same consulting brief, a tool-by-tool review with example slides, and a comparison table you can use to pick the right tool for your use case.

Three ways to generate consulting slides with AI

In our view, AI slide tools for consulting slides fall into three general groups:

1. Specialized consulting slide generators such as Perceptis, Oria and Xavier AI. These tools are built specifically for strategy consultants. They promise MECE storylines, action titles and the dense, chart-heavy slides you see in McKinsey or BCG decks.
    
2. General AI slide generators such as Gamma and Plus AI. These tools are built for anyone who needs a presentation quickly. They focus on visual design, templates and speed.
    
3. General-purpose AI models such as Claude and ChatGPT. These are the large language models themselves, which can now read a source document, plan a storyline and produce an editable PowerPoint file directly in the chat.

As mentioned, when we ran our first test in May, none of the tools could produce client-ready slides but the specialized tools came closest. The general purpose slide generators often couldn’t produce actual .pptx files and struggled with charts, which are a significant component in any consulting deck.

Since then, the large AI labs have made significant progress on slide generation, with the release of Claude Fable 5.1, Claude Opus 5.5, and GPT-6 Astra as some of the real differentiators in the slide space. That raises a practical question for anyone who makes decks for a living: do you still need a specialized slide tool, or is the model you already pay for good enough?

How we tested the tools

We gave every tool the same input and the same instruction, and judged the output the way we would judge a junior consultant’s first draft. We deliberately wanted to focus on the various tools' ability to turn data into slides (as opposed to doing research and analysis) so we used a full report as the input.

The source document: A 28-page public industry report, the China Juice Market Report published by Citrus Australia in January 2024. It contains market sizing, import data, competitor profiles and a consumer survey. This is typical raw material for a market analysis deck.

The prompt: “Turn this report into a consulting-style deck, similar to what McKinsey or BCG would produce.” We kept it deliberately short. Where a tool asked follow-up questions, we accepted its recommended option.

The tools and versions:

• Perceptis (web app, Starter plan)
• Oria (run through its Claude connector, Opus 5.5)
• Gamma (web app)
• Plus AI (both the web app and the PowerPoint add-in)
• ChatGPT (GPT-6.1 Sol, High reasoning)
• Claude (Opus 5.5 in Cowork, output in Claude Slides)

The criteria: we used the same four criteria as in our May test, plus cost.

1. Storyline quality: Does the deck make an argument, with an executive summary and action titles that state the “so what”? (See our guides on executive summaries and action titles.)
    
2. Slide-level quality: Are layouts clean, consistent and data-led? Is anything cut off, overlapping or left as a placeholder?
    
3. PowerPoint readiness: Can you get an editable .pptx file with native charts and text?
    
4. Time to generate: Wall-clock minutes from submitting the prompt to a finished deck.
    
5. Cost: What you need to pay to produce a deck of this size.

The ultimate bar to pass: Would we send this to a client after 30 minutes of clean-up?

Results: Specialized consulting slide generators

Perceptis

Verdict: A sound storyline let down by dated, poorly formatted slides. Not close to client-ready.

This was one of the best tools in our previous test, so we were excited to see how it would do. 

Perceptis generated a 20-slide deck in 11 minutes. The storyline is fine and most slides have a proper action title (“Supermarkets capture 61% of juice sales but e-commerce is the fastest-emerging channel”) and sourcing.

The problems are at the slide level:

• Old-school visuals: The deck leans on 3D isometric illustrations (a traditional Chinese medicine shop, stylised juice bottles) and stock product photos, as well as dark takeaway boxes on nearly every slide. This makes it look outdated and an outside-in view of what consulting slides look like, rather than actual slides from McKinsey, BCG, and Bain.
   
• Formatting errors: On the executive summary, the column headings overlap the body text. On the “Tea beverage shops” slide, four of the five bubbles are empty grey circles with a dash where the number should be. Some of the slides struggle with spacing and visual balance, with too much white space under the slide content, or a distracting mix of font sizes.
   
• Few good charts: Only a handful of slides use data charts. Four of the 20 slides are section dividers.

Cost and workflow: The Starter plan costs $29 per month for 50 slide credits, and one slide uses one credit. This single 20-slide deck used 40% of the monthly allowance. The next tier, Pro, is $129 per month for 100 credits. Perceptis exports a native .pptx and offers a PowerPoint add-in.

Oria

Verdict: Chart-heavy and data-rich, but slides look assembled rather than designed. Not close to client-ready.

Oria does not run as a standalone app in this workflow. It works as a connector inside Claude, so you need a Claude subscription on top of Oria’s own tokens. Before building, it asked three good questions: which storyline to argue (it recommended an “Australian exporter lens”), which visual style to use, and how long the deck should be. It then produced 12 slides in 19 minutes, the slowest run in the test.

The storyline is reasonable. It opens with an action-titled executive summary and closes with a phased entry recommendation (validate, enter, scale), and the slides inbetween are data-driven and thorough.

The slides are chart-heavy, which is the right instinct for consulting slides, but the execution is weak:

• Inconsistent typography: Font sizes vary from slide to slide and within slides. Chart labels in particular jump between sizes.
   
• Overcrowding: Several slides squeeze three charts and an implication box into one page, with very little spacing.
   
• Broken chart elements: Doughnut chart labels overlap the segments (one reads “4 0…”), and a stacked flavour bar renders with its labels on top of each other.

Cost and workflow: Oria charges in tokens: 40 tokens cost $10. Rendering our 12-slide deck required 12 tokens, and exporting it as editable PowerPoint required another 12. Our account ran out of tokens mid-build, and Oria offered to cut the deck to seven slides as a PDF unless we topped up. Budget roughly $6 per 12-slide editable deck, plus your Claude plan.

Results: General AI slide generators

Gamma

Verdict: The fastest and most polished design in the test, but built for marketing and internal decks, not consulting deliverables.

Gamma generated a 20-slide deck in a few minutes, with the most user-friendly interface of any tool we tested. It’s clear that Gamma is a visual-first product. The deck uses simple charts, large headline numbers and full-bleed photos for visual variety.

To its credit, the titles are mostly real action titles (“Imports more than tripled in volume since 2013 while the average price fell”), and every chart carries a source line. As a marketing report or an internal team update, this deck would work almost as is.

It does not look like an MBB deck, however, for two main reasons:

• Decorative color: Each bar in a chart has a different colour (teal, lime, coral, navy) with no meaning attached. Consulting decks use color to highlight the one data point that matters.
   
• Thin analysis: Large sections of the source report, such as the competitor profiles, are reduced to a single chart or a divider slide.

Cost and workflow: The free plan generates up to 10 slides per prompt, so you need a paid plan for a 20-slide deck. Gamma exports to PowerPoint, Google Slides, PDF and PNG.

Plus AI

Verdict: Text-heavy, repetitive slides with visible formatting errors. Not client-ready.

We tested both Plus AI’s web app (about 2 minutes to generate 20 slides) and its PowerPoint add-in (about 8 minutes for 16 slides).

The web version produced a deck with sensible action titles and a closing “four strategic implications” slide but visually, it’s weak. Most slides follow the same template of blue header bars, bullet lists and a single blue bar chart, so the deck feels monotonous by slide five. Formatting errors are frequent with things like section labels (“SUMMARY”, “COMPETITION”) print on top of the slide titles, and several titles run into the subtitle below.

The add-in output is cleaner. The overlapping labels are gone and charts sit better on the page. Unfortunately, it keeps the same core issue with too much text per slide and too little variety in how evidence is shown.

Cost and workflow: Plus AI’s Basic plan ($15 per month) does not allow file uploads, so you need Pro ($25 per month) or Team ($40 per month) to turn a report into a deck. Output is native PowerPoint or Google Slides.

Results: General-purpose AI models

ChatGPT (GPT-6.1 Sol)

Verdict: Clean and accurate, but too light and repetitive to pass as a consulting deck.

ChatGPT generated a 16-slide .pptx in 10 minutes. The deck represents the structure of the source report faithfully, and the numbers we spot-checked were correct. It also adds useful analysis the report does not contain, such as a calculated 14.1% import volume CAGR, and labels its recommendations as “analyst hypotheses”.

The weakness is in depth and variety. Titles mostly describe the data (“Seven established brands capture 73% of the juice market”) rather than state what it means for the client. Almost every body slide uses the same layout: one simple bar or line chart on the left and a large callout number on the right. A real consulting deck uses a much wider range of slide types (tables, driver trees, matrices, roadmaps) depending on the argument each slide makes.

Cost and workflow: Included in a ChatGPT subscription. Output is a downloadable .pptx file.

Claude (Opus 5.5)

Verdict: The strongest out-of-the-box deck in the test. Good content, balanced visuals, but not yet client-ready.

Claude asked two clarifying questions before building (storyline angle and deck length), then produced a 17-slide deck in 11 minutes.

The content is the best of the six tools. The executive summary follows the Situation-Complication-Resolution structure and ends with a clear recommendation. Titles are genuine action titles, footnotes explain where figures were estimated, and charts use a restrained palette with one accent colour for the data point that matters.

The main weakness is spacing. Many slides leave a large empty band below the slide body, which makes them look off-balance and unfinished. It doesn’t yet look like a McKinsey or BCG client deliverable, but it is the closest of the tools a reader could use without additional help.

Cost and workflow: Included in a Claude paid plan. Output is an editable deck in Claude Slides that downloads as .pptx.

Extra test: What happens when you give Claude some extra consulting tips and references?

For comparison, we also ran the same prompt through Claude using our own Slideworks setup: the Slideworks slide master plus a reference pack of consulting slides from our library and some small skill files. The model, prompt and source were identical.

The output was the closest to a real McKinsey or BCG deck of anything we tested, and could be sent to a client after only minor, quick touch-ups. The remaining fixes were cosmetic: a “Company Name” placeholder in the footer and an empty closing slide.

The difference came from references, not from a better model. This is consistent with what we see in our own internal testing: a strong model given good examples of what “great” looks like beats a strong model given only a prompt. In later articles, we’ll show you in more detail how to replicate this setup.

Which method should you use to create consulting-level slides?

Based on our test, there are three tips to creating AI consulting slides:

1. For consulting-style deliverables, start with a general-purpose model, not a specialized slide generator
   Claude produced a better storyline and cleaner slides than both consulting-specific tools, at no extra cost beyond a plan many teams already have. The specialized tools still charge per slide or per token for output that needs more rework. In our opinion, the additional cost is not worth the output.
    
2. For marketing, internal updates and visual-first decks, use Gamma
   If the goal is a good-looking deck in a few minutes, and nobody will judge it against an MBB standard, Gamma is the fastest route to a near-finished result.
    
3. Whatever tool you use, give it references
   The largest jump in quality in our test came from adding consulting reference slides and a proper master, not from switching tools. If you have a library of strong past decks, attach a few as examples and ask the model to use them as references.

Comparison table of AI tools for consulting slides

Tested 2-5 October 2026 with one source document and one prompt per tool. Prices as listed on each vendor’s site at the time of testing.

Conclusion

AI slide tools have come a long way since our first test in May. For design-forward, simpler presentations, you can paste in a document and the output will be near-finished. For consulting-style, client-ready decks, none of the tools gets there from a prompt alone but they are definitely getting much closer. General-purpose models such as Claude now produce the best starting point, and adding strong consulting references and a skill file closes most of the remaining gap.

In the coming weeks, we will publish detailed one-on-one tests of individual tools, including Claude versus Perceptis and Claude versus Oria, with full slide-by-slide outputs.