Table of Contents
- The Shift to AI‑Powered Vendor Research
- The 5 Patterns We See in Buyer Questions
- How ChatGPT Shortlists (and Why That Matters)
- The Sources ChatGPT Trusts for AI Vendor Research
- 4 Actions AI Vendors Must Take Right Now
- How PADISO Turns Buyer Questions into a Competitive Moat
- What PE Firms Should Know About AI Vendor Research
The Shift to AI‑Powered Vendor Research
B2B buying has changed faster in the last 18 months than in the previous decade. Your next prospect is not clicking through your website’s case‑study carousel or sitting through a cold demo. They are opening ChatGPT, Claude, or a corporate‑sanctioned gen‑AI tool and asking blunt, zero‑context questions like, “Who are the best fractional CTO firms for a $200M logistics company that needs to consolidate tech after an acquisition?” or “Is agentic AI actually worth it for mid‑market manufacturing, or is it just hype?”
A 2025 study reported that 90% of B2B buyers now use ChatGPT for purchasing research, with one in four using generative AI more often than conventional search. By 2026, 94% of B2B buyers will be using AI for vendor research, and generative AI will rank as the most meaningful information source for purchase decisions. The old playbook—SEO, outbound, and stuffed‑lead‑form gated assets—is being replaced by a new reality: if you aren’t part of the answer ChatGPT gives, you don’t exist.
At PADISO, we have been tracking this shift firsthand. As a founder‑led venture architecture and AI transformation firm, we partner with mid‑market brands, private‑equity portfolios, and venture‑backed startups. Over the past year, more than half of our inbound conversations have started with a variation of, “I asked ChatGPT who could help with [X], and you came up.” That is a wake‑up call for any AI vendor still relying on 2019 go‑to‑market tactics.
This article is a set of field notes—patterns in the questions buyers ask, what those questions reveal about their real fears and priorities, and how firms like ours can (and must) position themselves to be the answer, not the footnote.
The 5 Patterns We See in Buyer Questions
After analyzing over 300 initial‑contact emails, discovery‑call transcripts, and AI‑prompt snapshots that prospects have actually shared with us, five distinct patterns emerge. They align closely with the buyer‑journey research published by Groew, but with a heavy tilt toward the operational and risk‑avoidance concerns of the mid‑market.
1. Problem Framing: “What Should I Even Be Asking?”
The most common opening gambit is not a request for a vendor list; it is an attempt to define the problem. Buyers type prompts like:
- “We just acquired three companies and have four different ERPs. Who can help us consolidate without a 24‑month SAP migration?”
- “Our board is pushing for AI, but we don’t have a CTO. What kind of help do we actually need first?”
These queries reveal that mid‑market operators and PE partners are drowning in complexity and lack internal executive technical leadership. They are using ChatGPT as a sounding board to crystallize the ask before they spend a dollar. This is where a fractional CTO becomes the immediate, logical answer—and ChatGPT often spots that match. When a buyer asks, “What kind of help do we need?” and the response includes a seasoned executive who can audit the tech stack and build a roadmap, the conversation shifts from “Should we hire an army of consultants?” to “Let’s bring in a fractional CTO who’s done this before.”
2. Education: “How Does Agentic AI Actually Work?”
Before buyers will talk to a vendor, they need to distinguish signal from noise. The market is saturated with claims about “agentic AI” and “orchestration layers,” and decision‑makers are bewildered. They prompt:
- “Explain agentic AI like I’m the CEO of a $50M CPG company.”
- “What’s the difference between AI automation and AI agents—and which one cuts payroll costs faster?”
These educational queries are pure opportunity for vendors that publish clear, no‑jargon, outcome‑oriented content. Our AI Quickstart Audit was designed precisely for this moment: a fixed‑scope, fixed‑fee two‑week diagnostic that tells a leadership team what to ship first, what to retire, and what 90 days could unlock. When ChatGPT’s training data includes transparent offers like that, the AI naturally surfaces them in response to educational prompts.
3. Evaluation: “Who Are the Real Players Here?”
Once the problem is framed and the technology understood, buyers pivot to shortlisting. They ask:
- “Top fractional CTO firms for mid‑market manufacturing in the Midwest.”
- “Compare PADISO vs. Thoughtworks vs. Slalom for AI transformation.”
Here, research confirms that AI does not rank vendors; it shortlists them based on third‑party consensus. If your firm has a thin digital footprint—no analyst mentions, no G2 reviews, no case studies on third‑party sites—ChatGPT will exclude you, not because you are inferior, but because it cannot corroborate your claims. This is exactly why we invest heavily in publishing detailed case studies and technical blog posts. Buyers evaluating vendors are hungry for evidence, not sales copy.
4. Deal‑Breaker: “What Could Go Wrong?”
The most jarring pattern is the risk‑scan. Buyers on the cusp of signing a six‑figure retainer will ask ChatGPT outright:
- “What are the complaints about [Vendor X]?”
- “Has anyone had a failed SOC 2 audit after working with [Vendor Y]?”
At PADISO, we lean into this. Our Security Audit (SOC 2 / ISO 27001) service is not about regulatory guarantees—no firm can promise that—it is about audit‑readiness through Vanta and pragmatic architecture. When a buyer’s AI research surfaces a record of clean audits and transparent security posture, the deal‑breaker question evaporates. Conversely, silence on security is interpreted as hiding something.
5. Final Check: “Are They Legit?”
The last question before outreach is often a credibility triangulation:
- “Who founded PADISO, and what’s their background?”
- “Has Keyvan Kasaei written anything on AI strategy?”
Founder‑led firms have an advantage here if they have built a public body of work. Our About page and Keyvan’s published thought leadership give ChatGPT ample signal to confirm credibility. For big‑brand consultancies, this final check is a formality. For boutique firms, it is existential. If your leadership team is invisible online, the AI will direct prospects toward competitors whose founders are active on LinkedIn, have bylines in industry publications, and host bootcamps or workshops.
How ChatGPT Shortlists (and Why That Matters)
A critical nuance for AI vendors: when buyers ask for “the best” or “top 10,” ChatGPT does not pull out a ranking. It summarizes the online consensus, acting as a credibility filter. This has profound implications.
First, traditional SEO foot‑traffic does not directly translate into LLM‑sourced leads. You can rank #1 for “fractional CTO services” on Google and still never appear in a ChatGPT response if the model’s training data lacks authoritative citations linking your brand to that topic. AI‑powered search relies on co‑occurrence and consistent mentions across diverse, trusted domains.
Second, the window of consideration is shrinking. The old buying process involved a long list of 10 vendors, reduced to 3 for a formal RFP. Now, AI‑assisted research often delivers a shortlist of three to five names directly, and buyers rarely look beyond them. If you aren’t on that initial list, you never receive the RFP. This makes presence in the AI’s “mental model” a binary gate, not a linear funnel.
For PADISO, this insight shapes everything. We ensure our services for platform engineering in regulated industries are described in the language of outcomes—HIPAA‑ready pipelines, GxP data platforms, ATO support for DC‑based govtech—because those are the phrases buyers type. We also maintain a visible footprint in the specific geographies we serve, such as San Francisco, Houston, Atlanta, and Washington, D.C., because mid‑market buyers still prefer proxies for domain expertise.
The Sources ChatGPT Trusts for AI Vendor Research
To show up in these shortlists, you must understand what the AI trusts. A practical framework from Simaia offers a four‑step process: build test prompts, analyze citation patterns, audit competitor appearances, and validate gaps. Applied to the AI‑services space, a clear hierarchy emerges:
- Analyst Reports & Recognized Experts: Gartner, Forrester, and McKinsey. Even if you are too small for a Magic Quadrant, being quoted as a subject‑matter expert in an analyst’s blog or webinar can seed a mention.
- Review Platforms: G2 and Capterra are disproportionately influential for B2B services. A small number of verified, detailed reviews can outweigh years of self‑published content. If you have never claimed your G2 profile, you are invisible to the AI.
- Forum & Community Content: Reddit threads (r/smallbusiness, r/private_equity, r/aws) and Quora answers are frequently surfaced because they contain unstructured, “real person” language that mirrors buyer queries. Friction AI has documented how sales‑call transcripts and support tickets can reveal the exact phrasings to target.
- Competitor Analysis: What are your competitors saying that gets them cited? If a rival’s white paper on “AI ROI in food manufacturing” keeps appearing, create a more specific, data‑driven alternative.
At PADISO, we apply this daily. We track which prompts surface us versus surface the big consultancies and adjust our content strategy accordingly. For instance, when we noticed ChatGPT frequently pairing “CTO as a service” with “PE roll‑up” for deals in the $10–250M range, we doubled down on specific landing pages for Canberra and San Francisco that speak directly to board‑level concerns around speed, cost, and governance—the exact phrases that appear in the AI’s training corpus.
4 Actions AI Vendors Must Take Right Now
The window to establish LLM‑era discoverability is closing as more firms recognize the game has changed. Based on what we’ve observed—and stress‑tested with our own inbound engine—here are four immediate, non‑negotiable actions.
1. Get into the Right Analyst Reports
If you are a $2–10M services firm, you may not have the budget for a Gartner subscription. But almost every analyst shop needs guest contributors, webinar panelists, or “vendor to watch” nominees. Provide sharp, data‑driven quotes for their research notes. The goal is not a logo on your homepage; it is a mention that gets picked up by ChatGPT.
2. Leverage G2, Capterra, and Peer Review Sites
As the PresenceKit guide outlines, review platforms are among the heaviest‑weighted sources for B2B AI evaluations. Ask your best clients to leave a review—specifically mentioning the problem you solved and the measurable outcome. Structure the review to answer the “What could go wrong?” prompt in advance: “They helped us pass SOC 2 on the first try and cut cloud costs by 30%—no surprises.”
3. Create Content That Answers These Questions Directly
Stop writing “10 Benefits of AI” blog posts. Write the exact answer to a buyer’s framing question: “Here’s how a $50M logistics company consolidated 4 ERP instances in 6 months using Azure and a fractional CTO.” Publish it in multiple formats—long‑form article, downloadable PDF, a 10‑minute YouTube walkthrough—because ChatGPT ingests transcripts and text equally. Our blog follows this pattern, and it’s the primary reason buyers tell us “You came up in my research.”
4. Monitor and Engage on Reddit and Quora
This is where founders often recoil, but the data is undeniable. When a buyer types “scared my AI project will blow up,” they are often on Reddit. An employee or the founder in those threads—not selling, but genuinely helping—creates permanent artifacts that LLMs index. Do not outsource this to an intern; the nuance of a principal replying with “We handled a similar issue for a PE‑backed manufacturing roll‑up last month; here’s what we learned” is worth more than a thousand generic backlinks.
How PADISO Turns Buyer Questions into a Competitive Moat
The five question patterns aren’t just an academic exercise for us—they are the operating system for our service design. Here’s how each leads directly to a PADISO engagement.
Problem Framing → AI Quickstart Audit. When a buyer doesn’t know what they need, our two‑week fixed‑fee AI Quickstart Audit removes all friction. For AU$10K, we deliver a frank diagnostic, a prioritized roadmap, and a clear answer to the board’s “What now?” question. The offer’s specificity—fixed scope, fixed fee, no six‑month consulting engagement—makes it a natural answer for ChatGPT when it searches for “first step in AI transformation for mid‑market.”
Education → Fractional CTO as a Service. Buyers asking “What’s agentic AI?” need more than a textbook answer; they need someone who can sit across the table from their board and say, “Here’s the model that will actually move your EBITDA in 90 days.” Our CTO as a Service offering puts a seasoned, founder‑led executive—not a junior consultant—inside your leadership team, typically on a $100K–$500K retainer. We have dedicated fractional CTO pages for specific markets because we know buyers filter by region first, capability second. Whether you’re a biotech in Boston needing GxP‑aware architecture or a payments firm in Atlanta requiring PCI‑aware data platforms, the answer is hyper‑specific—and ChatGPT rewards specificity.
Evaluation → Venture Architecture & Transformation. When a PE firm compares PADISO to a Big Four, they aren’t just checking credentials; they are asking, “Who can move fast enough to show results before the next board meeting?” Our venture architecture and transformation practice is built for that: we ship agentic AI products, modernize on the public cloud (AWS, Azure, Google Cloud), and deliver measurable AI ROI within the first quarter. The proof is in the work, which we document publicly so that tools like ChatGPT can cite real outcomes.
Deal‑Breaker → Security Audit (SOC 2 / ISO 27001). The fear of a failed audit is visceral, especially for companies handling regulated data in healthcare, energy, or government. We address it head‑on with a security audit readiness service that leverages Vanta and deep regulatory expertise. In Houston, for example, our work with energy and aerospace teams has included HIPAA‑aware pipelines and industrial/OT architectures that pass diligence without drama. When a buyer asks ChatGPT, “Who can help us prep for ISO 27001 without derailing our cloud migration?” the answer includes firms that have publicly demonstrated that capability.
Final Check → Founder Authority. Keyvan Kasaei’s decision‑making is visible across every engagement, but also in the thought leadership and educational bootcamps PADISO runs. Our About page highlights over 50 businesses served and $100M+ in revenue generated through strategic AI implementation—not as vanity metrics, but as the kind of third‑party‑verifiable signal that LLMs prioritize when a buyer asks, “Are these people for real?”
What PE Firms Should Know About AI Vendor Research
Private equity operating partners are among the most sophisticated and brutal users of AI in vendor research. They have a clear, unforgiving agenda: identify the firms that can do tech consolidation for portfolio efficiency, drive EBITDA lift through AI, and not require six months of hand‑holding.
We’ve seen PE firms prompt:
- “List fractional CTO firms that have done post‑acquisition tech consolidation for roll‑ups in the $50–$200M range.”
- “Which AI transformation firms have experience with PE timelines (90‑day sprints, not 12‑month roadmap theater)?”
If your firm’s digital footprint is full of generic “digital transformation” language without hard numbers, you will be filtered out. PE buyers want specificity: “We consolidated five HR systems into Workday, migrated the combined entity to Azure in 10 weeks, and cut run‑rate tech spend by 18%.” At PADISO, we actively seek these opportunities—our entire model is designed around the pace and accountability PE firms demand. Our CTO advisory in Washington, D.C. and platform engineering in Atlanta are explicit about FedRAMP, ATO, and real‑time risk pipelines because those are the terms that appear in PE‑generated AI queries.
The message to PE firms is simple: when your portfolio company’s CEO asks ChatGPT for an AI vendor, make sure the answer they get is a firm that understands your value‑creation clock, not a consultancy that thinks “urgent” means a status call next week.
Conclusion: Where to Start
The buyers are already talking to ChatGPT about you—whether you like it or not. The only choice is whether you will be the answer they hear or the blank space they skip over. The patterns we’ve laid out are not speculation; they are field notes from real conversations, real prompts, and real revenue.
Start with an audit—of your own digital discoverability. Open ChatGPT (or Claude Opus 4.8) and ask it the questions your prospects are probably asking: “Who’s the best fractional CTO for a $100M CPG company on the West Coast?” or “What’s the real ROI of agentic AI for a mid‑market manufacturer?” If your firm doesn’t appear in the top five responses, you have work to do.
The good news: the playbook is still writable. Unlike Google’s opaque algorithm, LLM responses are remarkably predictable once you understand the source hierarchy. Invest in analyst visibility, build a review‑platform presence, publish outcome‑specific content, and let your founder’s voice be heard in the forums where buyers gather.
At PADISO, we’re doing this every day—and we’re happy to talk through what we’re seeing with any operator or PE firm staring down an AI buying decision. Book a call and let’s discuss what AI can realistically unlock for your business within a quarter.