Articles by Robert Best
Survey: Manufacturers Embrace AI Tools to Speed Product Innovation
GenAI tools are slated for further investment in the next two years to help accelerate design and engineering processes. KEY TAKEAWAYS: 71% said GenAI tools are key in generating new product ideas. 90% expect GenAI tools to accelerate their design and engineering process. But 56% said their design and manufacturing processes are only “somewhat integrated”.
Literatur: Stadt als Falle
Auf eine irrwitzig unterhaltsame, winterliche Odyssee schickt Sven Regener seine Helden in »Frankie und Freddie«. Regeners siebter Roman schließt an »Wiener Straße« und »Glitterschnitter« an, funktioniert aber auch für sich genommen. Er schildert einen einzigen Tag im Leben zweier Bremer Brüder in Berlin-Kreuzberg. 23. Dezember 1980: Frank Lehmann möchte seinen großen Bruder Manfred aus dem »Pillenhotel« am Kurfürstendamm abholen, wo der sich als Versuchskaninchen für Psychopharmaka verdingt hat.
The Scaling Constraint: Trusted Operational Information
KEY TAKEAWAYS: OT technical debt often remains hidden until operational data must scale across sites, systems, and business functions. Preservation of operational context and the consistent use of standardized definitions are foundational to scaling Manufacturing 4.0 initiatives. Reducing data friction requires governed definitions, operational context, and scalable information models, rather than control-system rewrites.
Volatile Markets Cost Fabricators Speed, Not Price
KEY TAKEAWAYS: The margin of damage isn’t determined at the negotiating table; it’s found in the lag between a cost change and a requote. Most AI pilots never reach production, and the reason is rarely the AI itself: It’s disconnected operational data. Fabricators that connect pricing, sourcing, and production data can reprice in hours—not weeks—and protect their margin while competitors reconcile spreadsheets.
Scale and Accuracy with the Buyer-Centric Smart Factory
KEY TAKEAWAYS: Manufacturers who maintain three separate definitions of the same configurable product create the exact friction that erodes speed and margin. A connected source of truth for configuration logic lets engineering, sales, and production work from one truth instead of reconciling conflicting versions after the fact.
The Value Leak: Why Digital Wins Fade After Go-Live
The technology works, but value quietly leaks through eroded trust, change fatigue and the human systems no one manages after go-live. KEY TAKEAWAYS: Value leaks not because technology fails but because the organization runs out of the human capacity to carry it. Sustainment is a leadership discipline: treat the workforce’s capacity for change as a finite constraint and measure adoption months out rather than at the moment a system technically works.
Protected: A Practical Approach to Physical AI in Manufacturing
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Upskilling the Manufacturing Workforce for AI
KEY TAKEAWAYS: Artificial intelligence and automation are transforming the nature of responsibility on the factory floor. Employees are moving from executing tasks to supervising and optimizing how work is performed by machines and AI. AI governance is becoming increasingly foundational as AI is embedded in operations. Manufacturers are under growing pressure to do more with a constrained workforce.
Welcome New Members of the MLC August 2026
ML Journal August 20, 2026 The Manufacturing Leadership Council welcomes its newest members. Ramsey Aljahmi COO EM Dynamics Read more ML Journal August 20, 2026 The manufacturers closing the productivity gap are augmenting automation with maintenance operations that are data-driven, predictive and connected. A pump fails on a Friday night. A technician shows up, diagnoses the problem from memory, fixes it in two hours, and goes home. No record of what he found. No documentation of what he did.
Embracing the Industrial Intelligence Era of Manufacturing
KEY TAKEAWAYS: Manufacturers must connect people, process, and technology to turn data into real operational outcomes. Digital and AI investments underperform without integration, governance, and a scalable operating backbone. Success requires building across five pillars that enable sustained, measurable transformation. Something fundamental is shifting in manufacturing.
Building An AI Governance Framework for the Factory Floor
TAKEAWAYS: ● While manufacturers are confident in AI’s potential, many are still determining how to govern it effectively. ● AI should be built on the same foundations as good corporate governance, IT governance and data governance. ● Manufacturers that establish practical, fit‑for‑purpose AI governance will be better positioned to scale AI capabilities. Governance for artificial intelligence tools and applications has become a practical requirement for any industrial company deploying AI at scale.
Managing Data Complexity with Trusted Hybrid AI
TAKEAWAYS: ● Trust in AI depends on explainability, especially when working with complex, high-risk manufacturing data. ● Generative and symbolic AI combine flexibility with deterministic logic to make complex data usable and reliably interpreted. ● Manufacturers can accelerate AI adoption by starting with targeted, explainable use cases rather than waiting for perfect data. Artificial intelligence (AI) is advancing rapidly across manufacturing, but adoption remains uneven.
TAKEAWAYS: ● Successful IT/OT integration requires a clear understanding of current personas, workflows, and capability gaps across both technical and operational domains. ● Technology investments should intentionally free up time for higher-value work and reshape responsibilities across IT and OT roles. ● A future-ready IT/OT structure must be adaptable to company size, talent availability, and evolving digital and operational technology needs.
Welcome New Members of the MLC May 2026
Latest Updates Welcome New Members of the MLC May 2026 Introducing the latest new members to the Manufacturing Leadership Council Penelope Brown April 30, 2026
TAKEAWAYS: ● As manufacturers increasingly adopt physical and agentic AI, they are prioritizing trust in these technologies. ● Given that safety is a key concern with physical AI systems, manufacturers should take precautions and operate these systems within a defined “safety envelope.” ● Because trustworthy AI depends on human accountability, manufacturers should preserve and enhance the trust already present in human-led processes.
Orchestrating Material Handling with AI & Automation
Email address Enter the 6-digit code sent to your email. Verification code TAKEAWAYS: ● A unified digital foundation enables scalable automation and AI, delivering measurable and repeatable value across an enterprise’s domains. ● Virtualization and dynamic digital twins reduce risk, accelerate deployment, and enable continuous optimization. ● Secure-by-design IT/OT architectures are essential for orchestrating data, automation, and AI safely and at scale.
Dialogue: Building Rheem’s AI-Ready Future
You can hear more from Joe Palomba at Rethink. Jeff Puma: Well, hello there everyone. I’m Jeff Puma, content director for the Manufacturing Leadership Council and I’m excited to be here for this Executive Dialogue. Joining me today is Joe Palomba, the senior vice president information technologies for Rheem Manufacturing. Joe, thanks for being here. Thanks for making time for this. Joe Palomba: Thanks, happy to be here. Jeff: Excellent.
Building An AI Governance Framework for the Factory Floor
TAKEAWAYS: ● While manufacturers are confident in AI’s potential, many are still determining how to govern it effectively. ● AI should be built on the same foundations as good corporate governance, IT governance and data governance. ● Manufacturers that establish practical, fit‑for‑purpose AI governance will be better positioned to scale AI capabilities. Governance for artificial intelligence tools and applications has become a practical requirement for any industrial company deploying AI at scale.
Managing Data Complexity with Trusted Hybrid AI
Skip to content TAKEAWAYS: ● Trust in AI depends on explainability, especially when working with complex, high-risk manufacturing data. ● Generative and symbolic AI combine flexibility with deterministic logic to make complex data usable and reliably interpreted. ● Manufacturers can accelerate AI adoption by starting with targeted, explainable use cases rather than waiting for perfect data. Artificial intelligence (AI) is advancing rapidly across manufacturing, but adoption remains uneven.
Dialogue: Building Rheem’s AI-Ready Future
Skip to content Jeff Puma: Well, hello there everyone. I’m Jeff Puma, content director for the Manufacturing Leadership Council and I’m excited to be here for this Executive Dialogue. Joining me today is Joe Palomba, the senior vice president information technologies for Rheem Manufacturing. Joe, thanks for being here. Thanks for making time for this. Joe Palomba: Thanks, happy to be here. Jeff: Excellent.
Orchestrating Material Handling with AI & Automation
Skip to content TAKEAWAYS: ● A unified digital foundation enables scalable automation and AI, delivering measurable and repeatable value across an enterprise. domains. ● Virtualization and dynamic digital twins reduce risk, accelerate deployment, and enable continuous optimization. ● Secure-by-design IT/OT architectures are essential for orchestrating data, automation, and AI safely and at scale. Material handling remains a significant constraint on global manufacturing.
Welcome New Members of the MLC May 2026
The Manufacturing Leadership Council is the world’s first member-driven, business leadership network dedicated to helping senior industry executives identify the opportunities created by transformational digital technologies in the operation, organization, and leadership of manufacturing enterprises as they pursue their journeys to Manufacturing 4.0. The National Association of Manufacturers (NAM) works for the success of the more than 12 million men and women who make things in America and...
Engendering Technology Trust in the Physical and Agentic AI Era
TAKEAWAYS: ● As manufacturers increasingly adopt physical AI and agentic AI, they are prioritizing trust in these technologies. ● Given that safety is a key concern with physical AI systems, manufacturers should take precautions and operate these systems within a defined “safety envelope.” ● Because trustworthy AI depends on human accountability, manufacturers should preserve and enhance the trust already present in human-led processes.
Kino: Ruhelose Seelen
Marina (Llúcia Garcia) hält sich am Rand und lässt sich begutachten Tiefes Blau, winddurchwehte Wuschelhaare, Haut, die schon beim Hinsehen nach Salz schmeckt – und Vigo. Die galizische Hafenstadt ist die heimliche Heldin eines ruhigen und wuchtigen Films, expressiv als wildromantisch rauher Küstenort inszeniert von Kamerafrau Hélène Louvart und Regisseurin Carla Simón. Simón, als Waise aufgewachsen, legt mit »Romerìa« den dritten Teil ihres Spielfilmzyklus zu Selbstfindung und Familie vor.
Survey: GenAI Adoption Surges as Manufacturers Continue to Grapple with Data, Skills Issues
Skip to content KEY TAKEAWAYS: ● 90% of manufacturers surveyed say they will increase generative AI usage in the next two years. Similar growth is expected for traditional AI tools. ● 67% say their companies now have a corporate AI strategy. ● But manufacturers are at an early stage on the maturity curve in their use of all types of AI systems.
Building an OT Organization in an IT World
Skip to content TAKEAWAYS: ● Successful IT/OT integration requires a clear understanding of current personas, workflows, and capability gaps across both technical and operational domains. ● Technology investments should intentionally free up time for higher-value work and reshape responsibilities across IT and OT roles. ● A future-ready IT/OT structure must be adaptable to company size, talent availability, and evolving digital and operational technology needs.
From Smart Factory to Smart Enterprise
TAKEAWAYS: ● Digital transformation in manufacturing is advancing in production and supply chain functions, but full value chain integration remains overlooked. ● Data maturity is a primary constraint preventing manufacturers from scaling smart factory investments. ● Workforce transitions are accelerating the need to digitize product knowledge, not just automate the factory floor. Manufacturers are investing heavily in digital production.
Practical AI Steps to Build Smarter Factories in 2026
Skip to content TAKEAWAYS: ● Modernize smart factories via digitization; choose technologies based on business outcomes and validate data availability before designing AI solutions. ● Prioritize use cases for business impact, short time‑to‑value, and data availability; target 60–90 day pilots that can scale. ● Embed AI into human operational workflows and governance so intelligence drives actions while people retain accountability and judgment.
Can AI Agents Catalyze Faster, Smarter Product Design?
TAKEAWAYS: ● AI agents speed product development by automating routine tasks and surfacing cross-system insights, helping teams avoid errors and make more optimized decisions. ● AI agents elevate human judgement rather than replacing it by surfacing relevant options and historical insights for designers to evaluate. ● Organizations that focus on targeted reuse scenarios, strong governance and clear KPIs will be best positioned to capture measurable impact from AI agents.
The Data-Ready Factory Starts With Trust
TAKEAWAYS: ● Manufacturers that treat data governance as a strategic capability gain measurable advantages in operational agility, forecast accuracy, and capital allocation. ● Interoperability is the prerequisite for autonomous decision-making, and organizations that cannot bridge their data silos see diminished returns on AI investments. ● Data mastery starts with shared definitions and ownership, aligning people, processes, and architecture before selecting any platform or technology.
Kino: Es gibt Probleme
Ein Ehepaar: Bühnenstar und Dramaturg (Özgü Namal und Tansu Biçer) Selfie mit dem Gouverneur im Foyer? Smalltalk mit der Istanbuler TV-Agentin? Nein, danke. Nach der umjubelten Premiere ihres neuen Stückes im Staatstheater Ankara relaxt Bühnenstar Derya (Özgü Namal) lieber backstage mit Flachmann und Zigarette. Dramaturg Aziz (Tansu Biçer), ihr Ehemann, muss die Verehrer vertrösten.
Dialogue: Leading Manufacturing Through AI Change
Skip to content David Brousell (DB): I’m David Brousell, the founder of the Manufacturing Leadership Council, the digital transformation arm of the National Association of Manufacturers. I’m here with Blake Moret, the chairman and CEO of Rockwell Automation. Congratulations, Blake, on becoming chair of the NAM this year. From your position as chair of the NAM as well as CEO of Rockwell, what is your sense of the state of the industry at this point in time?
Future-Proofing Business Amid Workforce Change
Skip to content TAKEAWAYS: ● The loss of experienced manufacturing talent creates a hidden commercial risk that impacts sales efficiency, accuracy, and growth. ● Manufacturers can reduce dependency on tribal knowledge by embedding product and pricing expertise into standardized digital processes. ● Guided, system-driven selling approaches help both sellers and buyers navigate complexity as workforce demographics continue to shift. Manufacturers are undergoing a pivotal workforce shift.
Third-Party Risk Management for Global Supply Chains
TAKEAWAYS: ● Companies should integrate risk management into their daily operations, rather than treating it as a standalone process. ● Advanced technologies allow manufacturers to map their supplier ecosystems with unprecedented depth and precision. ● Data organization and clear data governance are essential for modernizing third-party risk management processes.
Resilient IT/OT Architectures: Protecting Against Cyber and Operations Risk
TAKEAWAYS: ● Manufacturers must engineer resilience through secure-by-design, standards-based architectures that future-proof operations against connectivity failures. ● Edge AI ensures operational continuity by eliminating cloud dependency and preserving real-time decision support during disruptions.. ● Lasting cyber resilience requires commitment from IT and OT teams to collaborate and maximize risk reduction. .
Welcome New Members of the MLC February 2026
The Manufacturing Leadership Council is the world’s first member-driven, business leadership network dedicated to helping senior industry executives identify the opportunities created by transformational digital technologies in the operation, organization, and leadership of manufacturing enterprises as they pursue their journeys to Manufacturing 4.0. The National Association of Manufacturers (NAM) works for the success of the more than 12 million men and women who make things in America and...
Survey: Smart Factories Enter the Execution Era
Skip to content KEY TAKEAWAYS: ● Smart factories have entered the execution era with manufacturers now wrestling with how to scale digital transformation efforts ● AI is maturing beyond experiment into value-driven, smart factory deployments ● Digital transformation is shifting from table stakes to a game-changing advantage The Manufacturing Leadership Council’s 2026 Smart Factories and Digital Production Survey shows an industry that has moved beyond experimentation and into a more...
The Best of Executive Dialogue
The pace of change in manufacturing leadership has never been faster, and 2025’s Executive Dialogue series captured that shift in real time. Across conversations with industry trailblazers, a clear theme emerged: the future of manufacturing will be defined not just by technology, but by the leaders who know how to harness it.
MLJ December 2025 - Research Survey Recap
The Manufacturing Leadership Council has been devoted to using survey research to help take the pulse of digital transformation in manufacturing. Regularly surveying the operational leaders who are leading digital efforts in their companies has yielded insights into digital maturity levels, how advanced technologies are being used, what challenges manufacturers are having in embracing the digital model, and their aspirations for the future.
The Best of Rethink 2025
MLC members celebrated Rethink’s 20th anniversary by doing what they’ve done at the past 19 summits: learning about the technology, leadership, and organizations driving Manufacturing 4.0 forward. Over the course of three days, more than 60 speakers shared their insights during keynotes, case studies, panel discussions, (Re)Think Tanks, fireside chats, lightning rounds, and executive interviews. Here are a few of the exceptional sessions Rethink participants experienced.
The Best of 2025 Decision Compass Calls
The MLC’s Decision Compass groups are invaluable for discovering ways to level up your business. In 2024, these five groups explored a number of important M4.0 topics, including considerations for deploying generative AI; meeting the expectations of a multigenerational workforce; how operating data can predict equipment failure; managing supply variability with cloud technologies; and innovative ways to capture and reuse carbon emissions. These are just a sampling of what was featured in 2024.
MLC 2025 Photo Gallery
Skip to content MLC mektktktktktkttth anniversary by doing what they’ve done at the past 19 summits: learning About the author: Jtktktktktktktktma is Content Director for the Manufacturing Leadership Council View More
The Best of the Manufacturing Leadership Journal 2025
Skip to content As the manufacturing landscape continues to evolve, 2024 brought a wealth of insights, breakthroughs, and transformative ideas to the forefront. From exploring the practical applications of digital twins to harnessing the potential of Generative AI, the articles featured in this year’s best-of issue highlight the ingenuity driving Manufacturing 4.0 forward.
Welcome New Members of the MLC December 2025
Skip to content Learn more about MLC membership. Rodrigo Cambiaghi Managing Partner, EY Digital Operations EY https://www.ey.com/en_us https://www.linkedin.com/in/rodrigocambiaghi/ View More
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Dialogue: Agentic AI Moves from Insights to Action
Agentic AI is shifting the conversation in manufacturing from simply generating insights to executing real-world tasks. Prasoon Saxena, global president and co-lead—Products Industries at NTT DATA, Inc., explains how this new class of AI is already helping companies slash engineering cycle times, support an overstretched workforce, and unlock new levels of productivity.
AI with Open and Scaled Data Sharing in Semiconductor Manufacturing
TAKEAWAYS: ● Smart Manufacturing leverages large volumes of industry-qualified data to orchestrate applications comprehensively at multiple operational scales, but data access remains a barrier. ● Data sharing combined with Data-first site strategies recognize the need to first process raw operational data into AI-ready data for any AI, machine learning, or digital twin application to work.
Mastering Manufacturing Data for Real Advantage
TAKEAWAYS: ● Manufacturers generate massive volumes of data across design, production, logistics, and service, but fragmented systems prevent its effective use. ● Reliable data requires a governance framework that prioritizes quality, availability, lineage, ownership, and integration health as non-negotiables. ● Achieving data mastery is a staged transformation—beginning with strategy and governance, piloted through early wins, and scaled with continuous monitoring.
Survey: Manufacturers See Data, Lack Strategy
KEY TAKEAWAYS: ● Manufacturers recognize that data is the essential fuel for digital transformation, but without governance and analytics, they lack the “map” to turn data into strategy. ● While many companies report measurable gains in efficiency, cost reduction, and decision-making from data use, nearly half still lack a corporate-wide governance plan and processes to ensure data quality.
AI Turns Data Governance into a Middle Market Advantage
TAKEAWAYS: ● AI is democratizing data governance, making it practical and impactful for middle market manufacturers. ● Clean data isn’t just technical hygiene—it’s a strategic advantage that drives operational efficiency and trust. ● Modern AI-powered platforms simplify governance, reduce errors, and bring governance directly into daily operations. AI is at the center of the modern manufacturing conversation.
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