This guide is for leaders of automation system integrators and controls solution providers: firms that design and commission PLC and SCADA systems, machine vision, motion and line automation, and that migrate aging control systems. Robot makers seeking manufacturer shortlists are covered in a separate article in this series; here robots are one technology among many that an integrator installs.
The short version
- Demand is spreading to new sectors: the J.P. Morgan and Control System Integrators Association (CSIA) survey (opens in a new tab) of February 2026 named data centers, defense, semiconductors, power and energy, and life sciences as the sectors with the strongest momentum.
- Labor is the business case: the Manufacturing Institute and Deloitte (opens in a new tab) estimate US manufacturing may need 3.8 million workers from 2024 to 2033, and 1.9 million of those jobs could go unfilled.
- Automation is a top spending priority: in Deloitte’s survey of 600 manufacturing executives (opens in a new tab), 46% ranked process automation and 37% physical automation as a first or second investment priority, and respondents reported 10% to 20% gains in production output from smart manufacturing.
- Most manufacturers are past pilots: in Rockwell Automation’s 2026 study (opens in a new tab) of 1,560 respondents, 59% were actively using smart manufacturing technology and only 18% remained in pilot mode.
- Vision projects are growing: North American machine vision transactions rose 8.8% in the second quarter of 2026, according to A3 (opens in a new tab).
Who hires automation integrators, and what is a client worth?
Operations and engineering leaders at manufacturers, and a good client brings repeat projects, upgrades and service work.
Deloitte found that smart manufacturing initiatives are owned by operations leaders, such as the chief operating officer, in 51% of companies, and by technology owners, such as the chief technology officer, in 38%. In practice a plant or controls engineer scopes the project, an operations leader owns the business case, and procurement runs the bid. Forrester (opens in a new tab) reports that a typical business purchase now involves 13 internal stakeholders and nine external influencers. For an integrator, those outside influencers often include the automation vendor’s sales team, a consulting engineering firm or a peer at another plant.
The reason clients call is usually people. In the National Association of Manufacturers’ outlook survey for the first quarter of 2024, cited in the Manufacturing Institute and Deloitte study, 65% of respondents named attracting and retaining talent as their primary business challenge. AMT, the Association For Manufacturing Technology, links rising automation demand (opens in a new tab) to “nearly half a million current manufacturing job openings.”
There is no public figure for an average integration project. The CSIA article cites a MarketsandMarkets projection that the US integrator market will exceed $9.2 billion by 2029. Our inference about client value: the first project, often a migration of obsolete controls or a single new line, is the entry point. The value comes from the next lines, the plant standards, the service agreement and the sister plants that follow when the first project goes well.
Where does AI search enter an automation project?
At the start, when an engineer frames the problem and builds a longlist of possible integrators.
Controls and plant engineers are a large part of the audience in the 2026 State of Marketing to Engineers (opens in a new tab) survey by TREW Marketing and GlobalSpec, with Elektor. Its figures show where they look before they shortlist anyone:
| Where engineers research a purchase (TREW and GlobalSpec, 2026) | Engineers |
|---|---|
| Use generative AI during the purchasing process | 69% |
| Routinely use generative AI platforms for purchase research (up 8 points) | 21% |
| Routinely research in online technical publications | 76% |
| Routinely research on supplier and vendor websites | 74% |
| Routinely use industry directory websites | 31% |
| Find an AI search summary usually enough, among those who notice one | 6% |
Forrester describes generative AI searches as the starting point for business buyers, followed by validation from their internal and external networks. That matches how integrators are usually chosen: an engineer gathers names from research, the automation vendor’s partner list and colleagues, then checks each one. Robot makers that sell through integrators face the same longlist; see how robot makers reach manufacturer shortlists.
Note one difference between the integrator and the client. Rockwell’s study found that 34% of operations are already AI-augmented. That is AI inside the plant, which integrators install. This article is about AI in the buying process, which decides who gets asked to install it. Plant software vendors face the same research stage, covered in how MES and IIoT platforms get found.
What do plant leaders ask when they look for an integrator?
Project questions that combine a platform, a process, an industry, a place and a business goal.
These examples are ours, written to show the pattern. They are not taken from buyer logs.
| Need | Illustrative question |
|---|---|
| Migration | “Integrators that migrate legacy PLC-5 controls to a current platform in Ohio, with minimal downtime” |
| Vision | “Machine vision inspection integrator for label and lot code checks in a pharmaceutical plant” |
| Credentials | “CSIA certified integrators near Houston for water treatment SCADA” |
| ROI | “What payback should I expect from automating a case packing line?” |
| New sector | “Controls integrators with data center electrical and cooling experience” |
| Risk | “How do I choose an integrator for an operational technology cybersecurity upgrade?” |
The ROI question is where many projects begin, before the buyer has decided to hire anyone. A firm that answers it clearly, with ranges, assumptions and the cases where automation does not pay back, gives an assistant something specific to cite.
How does an AI answer turn into an integration contract?
Through a longlist, a site visit, a paid study or proposal, a project, then service and the next line.
- Longlist. An engineer asks an assistant, a vendor’s partner directory or a colleague who can do the work. Firms named in AI answers, and in the pages those answers cite, join the list.
- Check. The engineer reads case studies, platform credentials, certifications, industries served and locations.
- Scope. A site visit and often a paid feasibility study or front-end engineering package. This is the first revenue.
- Proposal and project. A fixed-price or time-and-materials proposal, an ROI case for the operations leader, then design, factory acceptance testing, installation and commissioning.
- Service and expansion. Support agreements, training, upgrades and the next line or plant.
An assistant’s answer can shape the longlist and the first check, but nothing after the site visit. References, engineering depth, price and the vendor relationship decide the rest. Deloitte found that 65% of respondents ranked operational risk as a first or second concern about smart manufacturing projects, which is why proof of delivery matters more than claims.
What makes an assistant name one integrator over another?
Independent proof it can find for the exact project; the platforms document how they search, not how they rank firms.
Documented by the platforms: OpenAI says (opens in a new tab) ChatGPT search rewrites a question into one or more targeted queries sent to search providers, and that sites must allow OAI-SearchBot to be eligible. Google says (opens in a new tab) AI Mode runs multiple related searches through a “query fan-out” technique, and its guidance for site owners (opens in a new tab) says there are “no additional requirements to appear in AI Overviews or AI Mode” beyond normal search best practices. None of them say how they choose a firm.
Observed in our studies:
- Google rankings are not the whole story. In our study of AI citations and Google rankings, only 8.3% of the pages ChatGPT cited ranked in Google’s top 10 for the question, and 68.5% were not in Google’s top 100 for the question or for any of ChatGPT’s own searches. Our article on whether SEO still matters for AI search explains what that means.
- Independent mentions go with recommendations. In our brand entity study, the odds of being recommended rose 4.7 times with each tenfold increase in independent sites naming a brand in the cited pages. For an integrator, those sites are trade journals, vendor case studies and association pages.
- Assistants look for reviews. In our hidden searches study, ChatGPT looked for reviews in 46.2% of answers. Integrators rarely collect public reviews, so case studies, references and trade coverage carry more of that weight.
Our inference for integrators: the trust signals are the ones a plant engineer already checks. Platforms you are certified on, industries and processes you know, regulated work you have done, the region you serve, independent certifications such as CSIA’s audited program, and documented results. The CSIA describes its certification as validating an integrator’s business and management practices “through an independent audit.” Vendor partner status and certifications should be stated exactly, because buyers check them with the vendor.
What does an integrator lose when it is left out of AI answers?
Early project conversations, especially in new sectors where buyers have no integrator relationship yet.
We found no measurement of integration work lost to AI absence. The reasoning below is labeled:
- New sectors mean new buyers. The CSIA survey points to data centers, semiconductors and life sciences, and A3 data show robot orders from automakers fell 25% in the first half of 2026 while other industries grew. We infer that many of these buyers have no integrator on file and will research before they call. Warehouse projects show the same long research phase; see how warehouse automation vendors make shortlists.
- The ROI conversation happens without you. If an assistant answers the payback question with someone else’s case study, that firm frames the project.
- Wrong facts filter you out. An outdated platform list, an old office or a lapsed certification in an answer can remove you from a longlist. Our guide to fixing wrong brand information in AI answers covers how to trace the source.
- Talent and capacity are scarce on both sides. Integrators face the same retirement gap as their clients, the CSIA says. Our inference: a firm that attracts better-matched inquiries spends its limited engineering hours on work it is most likely to win.
How does GEO work for an automation integrator?
Generative engine optimization (GEO) helps AI assistants find, describe and verify your firm for the projects you want.
For integrators, the work usually covers:
- Capability pages by project type. Control system migration, SCADA, machine vision, motion, packaging lines, batch control, OT cybersecurity: what you do, on which platforms, in which industries, with typical scope and timelines.
- Credentials stated exactly. Vendor partner levels, CSIA certification, safety and quality certifications, licenses where required, matched to the issuer’s own listing.
- Case studies with numbers. Before-and-after throughput, downtime, scrap or labor hours, published with client permission. These are what an assistant can quote.
- ROI explainers. Honest pages on payback ranges, assumptions and when automation is the wrong answer.
- Independent coverage. Bylined articles in trade publications, conference talks, association awards and vendor case studies naming your firm. Engineers rank online technical publications as their top research source.
- Consistent directory profiles. Vendor partner directories, CSIA’s directory, LinkedIn and Google Business Profile with the same name, offices, platforms and industries. Machine shops follow the same rule, keeping one identity across Thomasnet, LinkedIn and Google Business Profile, as CNC shops competing for RFQs shows.
- Measurement. Ask a fixed set of project, platform, industry and region questions across ChatGPT, Gemini, Perplexity, Copilot and Google’s AI features, repeatedly, and log who is named and what is cited. Our guide to designing AI visibility tracking explains how to set this up, then compare with project inquiries.
No integrator can be promised a mention. The aim is to make your firm the easiest to verify when a project is a genuine fit.
What can’t the data tell an integrator yet?
How many integration projects start with an AI answer, and how assistants rank integrators specifically.
- No attribution data. The surveys measure how engineers research. None links AI answers to integration contracts.
- Interested sources. Rockwell sells automation, CSIA represents integrators, A3 represents automation suppliers, TREW and GlobalSpec sell marketing to technical firms, and market-size projections come from commercial research firms.
- Our studies were broad. They tested buyer questions across several industries, not integrator searches, so carrying their results over to controls work is our own inference.
- Selection data is private. We found no public study, current and saveable, of how manufacturers choose between integrators.
Where should an automation integrator start?
Pick the projects you most want to win and ask assistants who can deliver them in your region.
Write ten questions the way a plant engineer would, naming the platform, process, industry and location, plus two or three ROI questions. Run them across the main assistants and record whether your firm appears, what it is credited with, which case studies and directories are cited, and which firms are named instead. That shows which proof is missing and where it should live.
If your next few years depend on winning more paid feasibility studies rather than chasing every bid, we can review how assistants present your integration firm. The review covers the migration, vision and line automation questions plant leaders ask, the integrators and partner directories that answer them today, and the case studies and credentials that would put your firm in those answers. How we then build capability pages, exact credential listings and trade coverage for an integrator is outlined on our generative engine optimization service page.
Frequently asked questions
Do manufacturers really use ChatGPT to find integrators?
Many engineers use generative AI somewhere in purchasing: 69% in the 2026 TREW and GlobalSpec survey. We found no data on integrator selection specifically, and referrals and vendor partner lists still matter.
Does being on a vendor’s partner list help in AI answers?
We have no direct evidence. Partner directories are outside sources that confirm your platforms and region, so keep them complete and consistent with your site.
Should we publish ROI figures from client projects?
Only with permission and with the assumptions stated. Specific, sourced results are more useful to buyers, and to assistants, than general claims.
Is CSIA certification worth stating prominently?
If you hold it, yes. It is an independently audited credential a buyer can check, which is the kind of fact assistants and engineers can verify.
Sources
- Industrial Distribution (2026), Integrators Remain Key Resource as Manufacturers Navigate Increasingly Complex Tech Landscape (opens in a new tab)
- The Manufacturing Institute and Deloitte (2024-04), Manufacturers Need as Many as 3.8 Million New Employees by 2033 (opens in a new tab)
- Deloitte (2025), 2025 Smart Manufacturing and Operations Survey (opens in a new tab)
- Rockwell Automation (2026-05-19), 90% of Manufacturers Say Digital Transformation Is Now Essential, According to New Global Study (opens in a new tab)
- Association for Advancing Automation (2026), A3 Vision & Imaging 2Q 2026 Abridged Report (opens in a new tab)
- Association for Advancing Automation (2026-08), Robot Orders Increase in Q2 as Automation Demand Broadens Across Industries (opens in a new tab)
- AMT via Automation.com (2026-07-13), $583.4 Million in New Machinery Orders Highlight US Economic Strengths (opens in a new tab)
- Forrester (2026-01-21), Forrester’s 2026 Buyer Insights: GenAI Is Upending B2B Buying (opens in a new tab)
- TREW Marketing and GlobalSpec (2026), State of Marketing to Engineers research report (opens in a new tab)
- OpenAI Help Center (2026), ChatGPT search (opens in a new tab)
- Google (2025-03-05), Expanding AI Overviews and introducing AI Mode (opens in a new tab)
- Google Search Central (2026), AI features and your website (opens in a new tab)
- Underneath (2026), Do ChatGPT, Gemini, Perplexity and Claude cite pages that rank?
- Underneath (2026), Do Wikipedia and schema make AI assistants recommend a brand?
- Underneath (2026), The hidden searches AI assistants run before they answer