Sercan Esen builds AI tools for workplace safety at Intenseye and works with manufacturing customers to understand safety challenges on the factory floor.
Sercan Esen is most useful for workplace safety AI field research and customer facing talks with manufacturing customers.
Best for
Fits workplace safety technology campaigns needing manufacturing customer field research or a customer facing webinar speaker.
Not for
Does not fit legacy EHS compliance and audit platform campaigns seeking public endorsement for a compliance suite.
Key takeaways
They argue safety is work design, not compliance monitoring, and light curtains cannot stop walking around.
They say EHS, operations, and IT must align, and tools should support decisions on the floor.
They report more than 35 internal AI agents shipped and 621 customer onsites since 2025.
Check first: Confirm partnership format, rates, and whether audience includes EHS or plant leaders.
Main ideas
Trust, not demos, is the test of a safety vendor · Redesign the hazardous step rather than asking workers to try harder · Plant visits are the research method, and the findings are specific
Sercan Esen builds AI tools for workplace safety at Intenseye and writes about applying them on manufacturing floors.
Their posts connect customer-site observations with questions about worker trust, human–machine collaboration, and whether safety technology helps frontline teams make better decisions.
They also say they contributed shop-floor perspectives to a World Economic Forum initiative on human–machine collaboration.
Readers interested in industrial safety, manufacturing operations, and applied AI will find a practical focus on how technology fits into the work itself.
Esen’s distinctive contribution is to frame safety as a problem of work design, not just compliance monitoring.
They argue that a light curtain cannot prevent someone from walking around it, and that understanding behavior can help companies redesign workflows to reduce workers’ exposure to hazards.
In another post, they draw five themes from reported customer conversations: EHS, operations, and IT need to align; tools should support decisions on the floor; and adoption depends on fitting into daily work.
Their account of visiting customer sites, observing work, and building what is missing makes the approach concrete, including the report that more than 35 internal AI agents had been shipped.
The posts pair field observations with company-focused product messaging, giving readers both operational ideas and promotional framing.
Esen writes about industrial safety from inside the work: repeated customer plant visits, conversations with EHS, operations, and IT leaders, then internal AI tooling built from what those visits reveal.
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Three arguments run through the posts.
First, safety technology matters only if workers trust it and leaders do not quietly bypass their own rules.
That trust comes from showing up on site again and again, not from showing a demo.
Second, safety innovation should change what is physically possible on the floor, removing risk at the source instead of adding administrative layers, reminders, or dashboards.
Third, field trips are not marketing; they are how Esen learns and builds the product pipeline: visit a site, watch the work, fly home, build what is missing, repeat.
Trust, not demos, is the test of a safety vendor
Esen argues that the more AI can do, the more customers want to know whether the vendor will be there, understand their world, and build with them.
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Their answer is presence: sitting in the same room, shaking hands, and returning repeatedly. In their World Economic Forum post, the same idea appears from the technology side: human-machine collaboration fails if frontline workers do not trust the systems or leaders quietly bypass their own safety rules.
Sercan Esen reports 621 customer onsites completed since the start of 2025, including 451 in the last twelve months and 143 in one quarter. They keep a personal map tracking visits to 26 of 50 US states, almost all for plant visits, and update it after every trip.
Redesign the hazardous step rather than asking workers to try harder
Esen says behavior is the real frontier of safety innovation.
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A light curtain can stop a machine, but it cannot stop someone from walking around it, so detection alone does not fix the problem.
The better move, in their account, is to redesign the step so the machine takes on the risk and the worker stays out of harm's way.
They report growing skepticism toward vague "proactive" and "predictive" claims and say the bar is rising toward engineered outcomes that remove risk at the source instead of adding an administrative layer or a reminder.
Automation, they argue, should remove exposure, not people.
The light curtain comparison, and the claim that you do not have to wait for backflipping robots to bring physical AI to manufacturing. Their shortest post pairs saving lives with stopping financial loss, treating safety as an operational cost, not just a compliance one.
Builders over slide decks, measured in shipped internal agents
Esen writes about building on planes between customer visits and late at night after days on the floor, and says better tools have cut some work from a month to a week.
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They report 35 or more internal AI agents live in production, some for teams serving customers and some for forward-deployed engineers in the field, and argue that agents do not replace builders but multiply them. Profiling work, in this telling, is done by people who show up on the floor and then sit down to build.
Esen credits cofounder Serhat Cillidag, named in the post as another constant builder, with shipping nonstop, separate from Esen's own output. The closing line: the hardest workplace safety problems are not solved in slide decks, and lives depend on what the team ships.
Safety data is operational data, so safety needs new roles and a strategy seat
Esen argues that in modern factories, safety data is operational data.
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When leadership treats it as a core data stream, safety teams become workflow architects and frontline workers become partners to the technology, rather than rule followers who hear about it only when something goes wrong. From that shift, they predict new industrial jobs, not just new tools.
Esen names three emerging roles: an EHS AI Specialist who tunes models, validates outcomes, and helps teams apply insights; a Safety Agent Supervisor who turns real-time safety signals into consistent action across shifts and sites; and a Human Machine Workflow Designer who shapes tasks, zones, and handoffs to reduce exposure. They say the roles are already appearing inside Intenseye's customer base and call preparing people for them one of the biggest workforce opportunities of the decade.
Compliance platforms have stalled; decisions matter more than dashboards
Esen says compliance still matters, but many EHS compliance platforms have not evolved: adoption is low, manual work is high, and workflows sit far from the floor.
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Some vendors relabel their products with "AI" without operationalizing the data into daily work, leaving the outcome unchanged, they say.
Their standard is adoption in practice: if a tool does not show up in daily operations, it becomes nice to have, and in manufacturing, nice to have gets cut.
Dashboards are not the ask, they write; decisions are.
The value lies in helping frontline leaders make the right call in the moment.
Esen quotes one EHS leader who said the last time they received a new feature from their EHS compliance platform was in 2017.
This is the clearest statement of what Esen argues about where industrial safety is heading, pitched at policy level rather than product level.
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A newcomer asking “is this a vendor talking or a thinker with a position?” should start here.
Esen writes that they joined the World Economic Forum to contribute to an upcoming Global Framework on Human–Machine Collaboration, bringing observations from Intenseye customer shop floors.
The post sets out five numbered points: human–machine collaboration starts with trust and fails if frontline workers distrust the technology or leaders quietly bypass their own safety rules; behavior, not equipment, is the frontier, illustrated by the line that a light curtain can stop a machine but cannot stop someone walking around it; three new industrial roles are emerging — an EHS AI Specialist who tunes models and validates outcomes, a Safety Agent Supervisor who turns real-time safety signals into consistent action across shifts and sites, and a Human Machine Workflow Designer who shapes tasks, zones, and handoffs; automation should remove exposure rather than people by redesigning a hazardous step so the machine takes the risk; and safety needs a seat at the strategy table because safety data is operational data.
The framework is described as launching in 2026, tied to WEF’s Frontline Talent of the Future and Next Frontier of Operations initiatives.
For brands planning a campaign
Build a webinar around one of the five points rather than a general “future of safety” theme.
The three emerging job titles in particular give the session a concrete, quotable structure the audience can act on.
A co-presenter from a customer site would match the post’s approach of grounding the framework in shop-floor observation.
This answers the practical questions of how Esen gathers field evidence and what came out of it.
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It’s the best single original post for judging whether the field research behind the speaking is real work or a marketing claim.
Esen opens with a travel and interview tally from three months: 22,487 miles, 11 states, 12 cities, 27 onsite visits, 16 customers, 12 industries, and 97 stakeholder conversations, split roughly into 47 EHS leaders, 32 operations leaders, 10 IT leaders, and about 5 CXO-level leaders.
Five patterns emerge.
First, EHS owns outcomes, operations owns reality, and IT scales it — alignment between the three accelerates execution, while misalignment stalls even well-funded programmes.
Second, hardware will matter more than people expect, with growing skepticism toward vague “proactive” and “predictive” claims and a rising bar for controls that remove risk at the source rather than add an administrative layer.
Third, EHS compliance platforms are being challenged: one EHS leader said the last new feature they received from their platform came in 2017.
Low adoption persists because workflows sit far from the floor.
Fourth, dashboards are not the ask; decisions are.
The value lies in helping frontline leaders make the right call in the moment.
Fifth, adoption is the strategy, not a metric, because anything that does not show up in daily operations gets cut.
They add that Intenseye completed 159 customer onsites in 2025, with more planned for 2026.
For brands planning a campaign
The five patterns make a ready-made agenda for a field research collaboration or recorded interview series.
Each is presented as an observation from named stakeholder groups, not as a statistic.
The 2017 platform-feature anecdote is a strong hook, but attribute it to one EHS leader rather than presenting it as market-wide data.
This answers whether Esen builds the technology or only speaks about it.
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For anyone weighing a technical webinar or product-adjacent collaboration, it establishes practitioner credibility.
Esen describes building on planes between customer visits and late at night after days on the floor, and says work that used to take a month now takes a week.
The post claims 35+ agents are live in production, running internally and supporting forward-deployed engineers in the field.
The stated working pattern is a loop: visit a customer site, watch the work on the floor, fly home, build what is missing, repeat.
They name Serhat Cillidag as “my cofounder” and credit them with shipping continuously.
The post closes with the argument that the hardest workplace safety problems are not solved in slide decks and that lives depend on what the team ships.
For brands planning a campaign
This supports a demo-led or build-along webinar rather than a purely strategic talk, and gives the host a specific question to ask Esen on stage: what did a site visit cause the team to build? The internal-agents detail also points to a concrete engineering audience alongside the EHS audience.
This answers what Esen considers proof of a customer relationship, which matters when judging how a partnership would run.
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It’s short, unusually concrete, and shows the working method rather than just describing it.
Esen reports 621 customer onsites completed since the start of 2025, with 451 in the last twelve months and 143 in a single quarter, described as the biggest yet.
The argument is that the more AI can do, the more trust matters, and that nothing answers the question “will you be there, will you understand our world, will you build with us?” better than sitting in the same room and showing up repeatedly.
They point readers to a personal map at sercanesen.com/on-the-road tracking 26 of 50 US states visited and invite comments or direct messages from anyone who wants a plant walk, noting 24 states to go.
For brands planning a campaign
The onsite count and public map give a field research collaboration a natural frame: a webinar can be pitched as one more stop on a documented tour, and the map gives the audience something to interact with. The direct invitation to request a plant visit is also a low-friction call to action a partner could echo.
This is the shortest possible introduction to Esen’s position: two sentences that frame the category against the more attention-grabbing robotics conversation.
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The post runs to two sentences.
The first contrasts waiting for backflipping robots with bringing physical AI to manufacturing now; the second is “Save lives and stop loss today with Intenseye.”
The framing pairs safety with financial loss rather than treating safety as a compliance cost.
For brands planning a campaign
A useful opening line or promotional hook for a session: it names the competing narrative and dismisses it quickly. The “stop loss” half is worth noting separately; it suggests promotional language aimed at operations and finance audiences, not only EHS teams.
Customer onsites as a research method and scoreboard3
Human–machine collaboration and frontline trust1
An explicit invitation for plant visits and field collaboration1
Building internal AI tools and agents from field observations1
EHS compliance platforms challenged; decisions over dashboards1
Workforce roles for AI-enabled safety1
Human–machine collaboration and frontline trust
In a post about contributing to the World Economic Forum's Global Framework on Human–Machine Collaboration, Esen argues that factories adding vision systems, advanced robotics, and autonomous equipment will not get safer if frontline workers do not trust the technology or leaders quietly bypass their own safety rules.
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They describe behavior as the real frontier of safety innovation: a light curtain can stop a machine, but it cannot stop someone from walking around it.
New technology can show how people behave in real time, explain why, and help redesign systems so workers naturally follow them instead of trying to defeat them.
The post also names emerging roles: EHS AI Specialist, Safety Agent Supervisor, and human-machine workflow designer.
For brands planning a campaign
For a customer-facing webinar, Esen can cover why AI safety adoption depends on trust, behavior redesign, and leadership consistency—not just detection. A workplace safety technology company can ask them to pressure-test rollout assumptions around worker trust, bypass behavior, and staffing for new safety roles.
Across three posts, Esen frames safety innovation as changing what is physically possible on the shop floor.
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One says companies do not have to wait for backflipping robots to bring physical AI to manufacturing and can save lives and stop loss today with Intenseye.
Another reports growing skepticism toward vague “proactive” and “predictive” claims, with the bar rising toward engineered outcomes that remove risk at the source rather than adding administrative layers or PPE reminders.
A third says automation should remove exposure, not people: companies are redesigning hazardous steps so the machine takes on the risk while the worker stays out of harm's way.
Esen advocates redesigning the hazardous step so the machine absorbs the risk, rather than asking workers to repeat it.
For brands planning a campaign
A safety technology company can evaluate Esen for content contrasting engineered controls with dashboards, compliance prompts, and vague predictive claims. A webinar could compare controls that remove exposure at the source with tools that add another layer on top of existing work.
Customer onsites as a research method and scoreboard
Esen publicly tracks customer onsite visits as a scoreboard.
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One post reports 621 customer onsites completed since the start of 2025, with 451 in the last 12 months and 143 in Q3 alone.
They also keep a personal map showing 26 of 50 US states visited, almost all for customer plant visits, updated after every trip.
A separate post reports three months that included 22,487 miles, 11 states, 12 cities, 27 onsite visits, 16 customers, 12 industries, and 97 stakeholder conversations.
Esen describes a repeatable pattern: visit a customer site, watch the work on the floor, fly home, build what's missing, and repeat.
For brands planning a campaign
For a field research collaboration, Esen's stated method is onsite observation with EHS, operations, IT, and CXO-level stakeholders. A workplace safety technology company can propose joint plant visits and customer discovery with a defined scope, participant mix, and output, then ask them to connect findings to product decisions.
An explicit invitation for plant visits and field collaboration
In the post reporting 621 customer onsites, Esen asks where to go next and invites readers to comment or send a direct message if they want them or an Intenseye team to walk their plant.
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They note 24 states still to go. This is an opening for plant-level engagement, not a generic speaker availability post.
For brands planning a campaign
A workplace safety technology company can respond to this invitation with a specific plant, region, or customer segment and a proposed joint research scope. Name the site and research question in the campaign ask, rather than simply requesting a webinar appearance.
Building internal AI tools and agents from field observations
Esen writes about building on planes, between customer visits, and late at night after long days on the floor.
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They say better tools have cut some build work from a month to a week and that 35+ internal AI agents are live in production, some for teams serving customers and some for forward deployed engineers in the field.
They name cofounder Serhat Cillidag as another constant builder and argue agents do not replace builders but multiply them.
The post ties the pattern back to customer sites: visit, watch the work, fly home, build what's missing, repeat.
They say the hardest workplace safety problems are not solved in slide decks but by people who show up on the floor and then build.
For brands planning a campaign
For a webinar or advisory engagement, Esen can discuss how field observations become internal AI tooling. A safety technology company can evaluate them on translating customer pain into operational agents and engineering workflows, not just presenting strategy.
EHS compliance platforms challenged; decisions over dashboards
In a field-trip analysis, Esen reports that EHS compliance platforms are being challenged.
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Compliance still matters, but they say many tools have not evolved; one EHS leader told them the last time they received a new feature from their EHS compliance platform was in 2017.
Esen points to low adoption, too much manual work, and workflows far from the floor.
Some vendors relabel with “AI,” they say, but without operationalizing data into daily work, the outcome is the same.
They argue dashboards are not the ask—decisions are: most teams already have reporting but lack fast, confident decision-making where reality happens.
“Adoption is not a metric, it is the strategy,” Esen says; if a tool does not show up in daily operations, it becomes “nice to have” and gets cut.
For brands planning a campaign
A webinar could focus on operationalizing safety data into frontline decisions rather than adding another headquarters dashboard. For advisory work, a safety technology company can ask Esen to assess whether a product fits how work actually gets done or adds another layer on top.
In the World Economic Forum post, Esen predicts industrial companies will create new safety roles in the next few years.
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These include an EHS AI Specialist, who bridges AI systems and daily operations by tuning models, validating outcomes, and helping teams apply insights; a Safety Agent Supervisor, who guides how real-time safety signals translate into action, coaches teams, and shapes consistent response across shifts and sites; and a human-machine workflow designer, who shapes how people and machines interact by designing tasks, zones, and handoffs that reduce exposure. They say these roles are starting to appear inside Intenseye's customer base and call preparing people for them one of the biggest workforce opportunities of the decade.
For brands planning a campaign
For a customer-facing webinar, Esen can discuss how buyers should staff and own AI-enabled safety systems rather than deploy tools with no operational owner. A safety technology company can evaluate them for workforce-planning content that connects new roles to shift-level adoption and consistent response.
Sercan Esen's posts revolve around Intenseye, the workplace-safety AI company they describe as co-founded, its customers, and the AI agents they build there.
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The other named organization is the World Economic Forum, where they say they joined to contribute to a framework on human–machine collaboration. For a campaign evaluating speaking and advisory work, the relationships have different implications: Intenseye is a founder-level tie that frames their speaking and advisory work, while the WEF contribution shows engagement with a standards body rather than a commercial arrangement.
Intenseye
Owned business
Esen writes about visiting “Intenseye customers,” refers to “my cofounder Serhat Cillidag,” and describes building internal AI agents and tooling for the company's forward deployed engineers and customer teams.
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The posts show a founder-level relationship but do not state a formal title or ownership stake; confirm those details if they matter to a campaign.
Esen says they joined the World Economic Forum to contribute to its upcoming Global Framework on Human–Machine Collaboration, sharing observations from Intenseye customer shop floors.
Sercan Esen’s posts sit where industrial safety meets AI in manufacturing.
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The recurring argument: safety technology works when workers trust it and work is redesigned so machines take on risk—not when another dashboard or reminder is layered on top.
Their field notes cover customer plant visits, conversations with EHS, operations, and IT leaders, and the internal tools built in response.
Start with posts on human–machine collaboration and behavior-based risk removal, then explore the trip reports and posts about building internal AI agents.
For safety program leadership, frontline workforce performance, or food safety culture, consider the similar creators below.
Regnier covers frontline industrial operations and argues that AI will not execute work until organizations make it structured, connected, and measurable, with the frontline feeding context back into the system.
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That aligns with Esen’s view that safety data is operational data and tools matter only when they integrate into daily work.
Regnier’s examples center on supply chain and warehouse operations—workforce performance, turnover, and AI readiness—rather than workplace safety technology. Esen anchors their arguments in safety risk, behavior, and plant visits; Regnier anchors his in operational execution and labor performance.
Masters builds safety culture by teaching preventive controls courses, speaking on food safety culture, and co-authoring practical guidance and tools.
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The focus on culture, training, and usable resources overlaps with Esen’s argument that behavior and trust—not just controls—determine outcomes.
Masters applies this to food safety in food and nut manufacturing, focusing on courses, conference sessions, and published guidance. Esen applies it to industrial workplace safety, physical AI, and the roles and tools that come with it.
For a customer-facing webinar or field research collaboration, Sercan Esen’s LinkedIn posts indicate reach and a clear topical fit with EHS, manufacturing, and operations audiences.
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Use the LinkedIn follower count as a rough measure of potential distribution, not as proof that EHS decision-makers, plant leaders, or safety buyers make up the following.
The posts are written for EHS and manufacturing leaders and repeatedly discuss safety technology, factory-floor adoption, and customer visits.
Selected examples: a post about joining a World Economic Forum framework on human–machine collaboration, a post summarizing 97 stakeholder conversations across manufacturing sites, and a post describing AI agents built for field teams.
To judge fit for a workplace-safety webinar, ask for recent post metrics broken out by audience role or an audience survey showing job function and seniority.
Sercan Esen's posts contain no sponsorship menu, media kit, rate card, or partnership inquiry page, so there is no published creator-partnership format to plan against.
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They show how Esen and Intenseye work with manufacturers: repeated customer onsite visits (one post counts 621 onsites completed since the start of 2025), an open invitation to request a plant walk by comment or direct message, and a contribution to the World Economic Forum's Global Framework on Human-Machine Collaboration.
These are company-level sales and research motions, not documented sponsorship offers; the posts give no pricing, deliverables, exclusivity terms, or lead times.
For a customer-facing webinar or field research collaboration, expect to negotiate terms directly and ask for a written scope covering audience, session format, data handling for any plant-floor research, and approval steps.
A workplace-safety technology company wants Sercan Esen as a customer-facing webinar speaker and field research partner alongside its manufacturing customers.
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This campaign is a close match for four reasons.
First, the audience is already the one Esen writes for.
The posts address EHS and manufacturing leaders directly, discussing safety technology, factory-floor adoption, and customer visits.
The company would be joining a conversation about industrial safety buyers, not borrowing reach from an unrelated following.
Second, Esen brings a developed position, not a generic theme.
The World Economic Forum post lays out five numbered points — trust first, behavior as the real frontier, three emerging safety roles, automation that removes exposure rather than people, and safety data as operational data — giving a webinar a ready structure the audience can act on.
The three named roles (EHS AI Specialist, Safety Agent Supervisor, human-machine workflow designer) are the posts’ most quotable material.
Pitched at workforce planning, they also offer a useful second audience alongside safety buyers.
Third, the field research rests on a stated method, not just a claim.
Esen counts 621 customer onsites since the start of 2025, with 451 in the last twelve months and 143 in one quarter; tracks plant visits on a public map covering 26 of 50 US states; and describes a repeated loop of visiting a site, watching the work, flying home, and building what is missing.
A separate post reports 97 stakeholder conversations split across EHS, operations, IT, and CXO-level leaders.
That makes Esen a strong fit for a joint research project: the posts show a habit of onsite observation across functions, not desk research or conference appearances.
Fourth, there is an open door.
The onsite post asks readers to comment or send a direct message if they want Esen or an Intenseye team to walk their plant, and notes 24 states still to go.
A specific proposal naming a site and research question answers that invitation.
The main constraints are commercial and practical.
The posts publish no sponsorship menu, rate card, or partnership inquiry page, so deliverables, pricing, exclusivity, and lead times would need to be negotiated.
The follower count is a rough distribution signal, but the posts do not show the professional roles or seniority of that following.
Ask for audience composition before promising the vendor’s customers a large EHS-decision-maker audience.
When to choose a specialist
A legacy EHS compliance and audit platform vendor wants Esen as the public face of a campaign promoting its compliance suite, with endorsement content aimed at existing customers.
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This is a poor fit because it would ask Esen to endorse a category they publicly criticize.
In the field-trip analysis, they write that EHS compliance platforms are being challenged and many tools have not evolved.
They report one EHS leader saying the last new feature they received from their platform came in 2017.
Esen links that to low adoption, too much manual work, and processes far from the floor.
They add that some vendors relabel with “AI” without putting data to work in daily operations, producing the same outcome.
They also argue that dashboards are not the ask — decisions are — and that anything which does not show up in daily operations becomes “nice to have” and gets cut.
A paid endorsement of a compliance-administration product would directly contradict those published judgments, and anyone searching the name would find the contradiction quickly.
The second problem is value.
Esen’s posts focus on engineered controls that change what is physically possible on the floor, real-time behavioral insight, and translating field observation into internal tooling.
They offer little support for a campaign about audit processes, compliance documentation, or reporting administration.
The audience argument would rely almost entirely on the follower count, which the posts do not break down by role or seniority.
A related weak fit points the same way: a robotics vendor campaign built around humanoid or “backflipping robots” would run against Esen’s framing, which contrasts waiting for that narrative with bringing physical AI to manufacturing now.
Check this message conflict against the vendor’s actual positioning before approaching; the posts do not describe that vendor’s products.
A worked campaign example
A safety technology company engages Esen for a customer-facing webinar and a joint field research sprint.
Session concept.
Title the webinar around findings from the floor, not AI in general — for example, “What 27 plant visits in three months told us about safety technology that actually gets used.”
Open with the two-sentence post contrasting physical AI with waiting for robots to establish the category position, then move to the five patterns from the field-trip post: EHS owns outcomes, operations owns reality, IT scales it; hardware will matter more than expected; compliance platforms are being challenged; decisions beat dashboards; adoption is the strategy.
Close with the three emerging roles from the World Economic Forum work, giving the audience a workforce-planning takeaway as well as a tooling one.
Format.
A build-along or demo-led session fits the posts better than a purely strategic talk.
Esen writes about building internal AI agents between customer visits, with 35+ in production, some serving customer-facing teams and some serving forward-deployed engineers.
The natural on-stage question is one their own post answers: what did a site visit cause the team to build?
A co-presenter from one of the host’s customer sites would reflect Esen’s method of grounding claims in the factory floor rather than the slide deck.
Field research scope.
Propose a defined sprint, not open-ended access: two or three named plants; a participant mix that matches Esen’s current work (EHS, operations, IT, and at least one CXO-level leader per site); a written research question for each site; agreed data handling for anything recorded on the floor; and a named output — for example, a public session at the next webinar plus a short internal readout for the host’s product team.
Ask for a plant walk, echoing Esen’s own call to action, and name the region so the 24 remaining states become a concrete offer rather than a general request.
Commercial terms to settle in writing.
The posts do not describe sponsorship formats, rates, or a partnership inquiry route, so negotiate terms directly.
A scope memo should cover session format and length, whether the host may reuse the recording, who owns research findings, any exclusivity window in the safety technology category, approval steps for quoting Esen’s plant counts, and lead time for travel.
Test the engagement against the campaign’s goals.
The webinar succeeds if attendees leave with one actionable decision, such as which controls remove exposure rather than add an administrative layer.
The research sprint succeeds if its findings lead the host’s product team to change something.
If the planned deliverable is a general “future of safety” panel with no named site and no product decision attached, the campaign would pay for Esen’s strongest published work — repeated onsite observation that turns into shipped work — without using it.
Choose Joe Renz when the campaign focuses on EHS software adoption and change management rather than plant-floor safety technology, or when the host wants a practitioner-dialogue format.
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Renz's strongest post for this buyer decision argues that the most expensive safety program is the one nobody uses: six-figure EHS software sitting at 20 percent adoption a year after go-live, with dashboards that look fine while the floor still runs on paper forms and email incident reports.
The stated cause is that implementation assumed people would adapt to the system instead of the system adapting to people.
The proposed benchmark: the newest operator on the floor can use the system on day one without training.
For a safety-technology vendor whose customers complain about low adoption of tools they already own, this is sharper and more specific criticism than Sercan Esen's broader claim that compliance platforms are being challenged.
Renz also uses a two-way format.
A question to EHS leaders about what a new EHS manager should ask in the first 30 days drew replies from Bradley York on whether corrective actions come out of the EHS budget, Michael Kary on asking everyone from the ground level to the CEO what gets in the way of making the safe choice, and Shannon Dickson Rand on who investigates incidents and who is accountable at the front line.
If the host wants a webinar where the audience supplies the content and the speaker structures it live, Renz has demonstrated that method.
Renz's posts cover a narrower topic and sit earlier in the buying conversation than Esen's.
They include two text posts about software adoption and interview questions, but show no onsite observation program, customer plant-visit count, named field-research output or joint research sprint with a customer's product team.
Renz reaches EHS managers and practitioners rather than the mixed EHS, operations, IT and executive group Esen says they convene.
A campaign seeking cross-functional findings from named plants would lose that structure.
If the host wants a co-presenter from its own customer sites or a research question tied to a product decision, ask Renz for evidence of that capability.
Choose Tim Regnier when the host's customers work in warehousing, distribution and retail supply chain rather than factory safety, or when the panel asks how organizations prepare frontline work for AI execution.
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Regnier's argument for this buyer task follows a readiness sequence: Gartner predicts 40 percent of agentic AI projects will be canceled by the end of 2027 while MHI data shows 65 percent of supply chain leaders plan to invest.
The stated reason projects fail is that organizations skip groundwork and jump to implementation.
The proposed fix is to make work AI-readable: map how work actually gets done, connect planning and execution systems to frontline activity, capture the daily exceptions people handle, and define what successful completion looks like, with the frontline inside the intelligence loop rather than receiving instructions from it.
A second post offers a concrete frontline-performance angle: fulfillment and distribution centers with 20,000 to 200,000 frontline workers gaining an average 4 percent quality performance improvement and hitting productivity goals weeks faster with new hires.
For a webinar about AI in industrial operations, this is a more developed explanation of why deployments stall than a tooling demonstration.
Regnier's domain is adjacent, not the same.
They write about warehouse operations, frontline workforce performance and supply chain execution; none of the posts addresses workplace safety, physical controls, PPE, incident investigation or EHS compliance.
A safety-technology vendor hiring a safety speaker would be paying for a translated argument rather than field evidence.
The posts also show no onsite program comparable to Esen's repeated plant visits or joint research with a customer's product team.
One of the two posts dates from 2022, so check the warehouse figures against current material before using them; the other offers a framework argument with no named sites.
Regnier is the better choice for a supply-chain operations audience and the weaker choice when the deliverable is safety-specific findings from identified plants.
Choose Yvonne Masters when the host's manufacturing customers work in food and nut processing, or when the campaign needs an accredited instructor and published co-author rather than a technology vendor voice.
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Masters approaches the same buyer decision—bringing outside expertise to a customer-facing session—from the food safety culture side.
The posts show a Preventive Controls for Human Food v2.0 course taught for food manufacturing employees, a presentation on creating the code on food safety culture at the Peanut and Tree Nut Processors Association Operations and Technical Food Safety Forum, a small-group exercise in which participants built actionable ideas for one nut manufacturer, and co-authorship of the Culture of Food Safety chapter in the association's handbook for the safe handling and processing of nuts.
Masters combines teaching and facilitation: they run a scenario with participants, then point them to written guidance and tools.
That is the closest match in this set to a working session rather than a talk.
Masters focuses on food safety culture and regulatory compliance, not AI-enabled industrial safety technology.
They would not carry a webinar on vision systems, engineered controls or real-time behavioral insight; Esen's specific claims about compliance platforms aging and dashboards giving way to decisions have no counterpart in these posts.
The posts cover conference speaking and classroom teaching, not repeated customer-site research.
If the campaign needs evidence from named plants, ask Masters for the plant-visit program, field-research scope or product-feedback loop.
Masters also teaches within a defined regulatory curriculum, making them a mismatch for a campaign seeking a vendor-neutral critique of the safety-technology category.
They are a better choice for a food and nut processing audience wanting credentialed instruction and a named chapter author.
This profile draws on five LinkedIn posts published by Sercan Esen, each read in full: a short post on bringing physical AI to manufacturing, an account of building internal AI agents, a post reporting 621 customer onsites, a summary of three months of plant visits and five recurring patterns, and a post on contributing to a World Economic Forum framework on human–machine collaboration.
The posts cover workplace safety, AI in manufacturing, customer visits, internal tooling, gaps in EHS compliance platforms, and emerging safety roles.
No publication dates came with the material, so ideas are grouped by theme rather than sequence.
World Economic Forum pages and a personal travel map that the posts link to were not included, so those figures and the framework's status appear as Esen stated them.
