Enthought, Inc.

01/08/2026

R&D doesn’t fail because teams lack ideas. It fails because too much time and money are spent validating the wrong ones. As generative AI floods R&D pipelines with possibilities, the real competitive advantage comes from knowing which paths not to pursue.

In this Forbes Technology Council article, Enthought COO Michael Connell explains why predictive AI is key to driving ROI in scientific R&D.

Read the full article here: https://www.forbes.com/councils/forbestechcouncil/2026/01/05/how-predictive-ai-works-as-an-roi-engine-for-rd/

True ROI for R&D won't come from the tool that generates 10,000 new ideas. It will come from the tool that confidently tells you which 9,990 to ignore.

11/12/2025

Agentic AI should be part of of every R&D leader's AI strategy, but change management is often the critical missing piece for ROI. Enthought's Michael Connell shares his perspective with CIO Online on how to prepare the workforce for an AI era: https://www.cio.com/article/4082282/preparing-your-workforce-for-ai-agents-a-change-management-guide.html

"𝘛𝘩𝘦 𝘣𝘦𝘴𝘵 𝘵𝘦𝘤𝘩𝘯𝘰𝘭𝘰𝘨𝘺 𝘥𝘦𝘭𝘪𝘷𝘦𝘳𝘴 𝘻𝘦𝘳𝘰 𝘷𝘢𝘭𝘶𝘦 𝘪𝘧 𝘯𝘰 𝘰𝘯𝘦 𝘶𝘴𝘦𝘴 𝘪𝘵, 𝘢𝘯𝘥 𝘢𝘥𝘰𝘱𝘵𝘪𝘰𝘯 𝘪𝘴 𝘵𝘩𝘦 𝘧𝘪𝘯𝘢𝘭, 𝘤𝘳𝘪𝘵𝘪𝘤𝘢𝘭 𝘮𝘪𝘭𝘦. 𝘓𝘦𝘢𝘥𝘦𝘳𝘴 𝘮𝘶𝘴𝘵 𝘯𝘰𝘵 𝘰𝘯𝘭𝘺 𝘣𝘶𝘥𝘨𝘦𝘵 𝘧𝘰𝘳 𝘤𝘩𝘢𝘯𝘨𝘦 𝘮𝘢𝘯𝘢𝘨𝘦𝘮𝘦𝘯𝘵 𝘢𝘴 𝘴𝘦𝘳𝘪𝘰𝘶𝘴𝘭𝘺 𝘢𝘴 𝘵𝘩𝘦𝘺 𝘣𝘶𝘥𝘨𝘦𝘵 𝘧𝘰𝘳 𝘣𝘶𝘪𝘭𝘥𝘪𝘯𝘨, 𝘣𝘶𝘵 𝘢𝘭𝘴𝘰 𝘪𝘯𝘷𝘰𝘭𝘷𝘦 𝘦𝘯𝘥 𝘶𝘴𝘦𝘳𝘴 𝘸𝘩𝘰 𝘢𝘳𝘦 𝘨𝘰𝘪𝘯𝘨 𝘵𝘰 𝘣𝘦 𝘵𝘩𝘦 𝘤𝘰𝘯𝘴𝘶𝘮𝘦𝘳𝘴 𝘰𝘧 𝘵𝘩𝘦 𝘵𝘦𝘤𝘩𝘯𝘰𝘭𝘰𝘨𝘺 𝘦𝘢𝘳𝘭𝘺 𝘢𝘯𝘥 𝘤𝘰𝘯𝘴𝘪𝘴𝘵𝘦𝘯𝘵𝘭𝘺 𝘪𝘯 𝘢𝘯 𝘢𝘨𝘪𝘭𝘦 𝘥𝘦𝘷𝘦𝘭𝘰𝘱𝘮𝘦𝘯𝘵 𝘱𝘳𝘰𝘤𝘦𝘴𝘴.
--- Michael Connell, COO, Enthought

Change management practices tailored to specific employee segments must be introduced early if your agentic AI strategy is going to deliver any positive business impact.

09/23/2025

In our latest webinar, Michael Connell breaks down the essential framework for implementing agentic AI in materials chemistry. Here's the key insight: success isn't just about the technology.

💡 "𝘞𝘩𝘦𝘯 𝘺𝘰𝘶'𝘳𝘦 𝘵𝘢𝘭𝘬𝘪𝘯𝘨 𝘢𝘣𝘰𝘶𝘵 𝘢 𝘣𝘶𝘴𝘪𝘯𝘦𝘴𝘴 𝘴𝘰𝘭𝘶𝘵𝘪𝘰𝘯, 𝘺𝘰𝘶'𝘳𝘦 𝘵𝘢𝘭𝘬𝘪𝘯𝘨 𝘢𝘣𝘰𝘶𝘵 𝘢 𝘴𝘰𝘤𝘪𝘰-𝘵𝘦𝘤𝘩𝘯𝘪𝘤𝘢𝘭 𝘴𝘺𝘴𝘵𝘦𝘮. 𝘐𝘵 𝘩𝘢𝘴 𝘵𝘦𝘤𝘩𝘯𝘰𝘭𝘰𝘨𝘺, 𝘣𝘶𝘵 𝘪𝘵 𝘢𝘭𝘴𝘰 𝘩𝘢𝘴 𝘱𝘳𝘰𝘤𝘦𝘴𝘴 𝘢𝘯𝘥 𝘩𝘶𝘮𝘢𝘯 𝘣𝘦𝘪𝘯𝘨𝘴."

This layered approach forms what we've found to be the "minimum viable toolkit" for successful agentic AI initiatives in materials science.

Watch the full discussion: https://www.enthought.com/webinar-agentic-ai-in-materials-chemistry-2025

09/16/2025

R&D leaders today face an ever-growing challenge: Which technical projects should we prioritize in the lab?

There are usually too many promising ideas competing for too few resources. Without a clear framework, R&D orgs risk wasting limited budgets, missing opportunities, and stalling innovation.

In new Forbes Technology Council article, Enthought's Michael Connell explores how a strategic roadmap avoids the costly trap of “everything is a priority” and introduces his Three-Swimlane Framework to help R&D leaders prioritize technical projects with clarity.

Read more 👉https://www.forbes.com/councils/forbestechcouncil/2025/09/12/the-magic-of-a-roadmap-how-to-prioritize-technical-projects-in-rd/

Fear of competitors leveraging AI successfully, coupled with significant investments required in talent, infrastructure and data governance, increases pressure to choose wisely.

09/05/2025

🤖 Agentic AI is disrupting materials and chemistry R&D, but it's easy to get lost in the jargon and hype. Join us for the upcoming webinar "Making Sense of Agentic AI: A Strategic Briefing for Materials & Chemistry R&D Leaders."

Enthought's experts will demystify agentic AI—what it is, why it matters now, and how to think strategically about adoption, impact, and long-term value in materials and chemistry R&D. This isn't another technical deep dive—it's a strategic conversation for leaders on why agentic AI is a game-changer for R&D organizations with practical guidance on how to get started.

➡️ Full details and registration link: https://events.enthought.com/agentic-ai-in-materials-chemistry-2025

Bonus! Registrants will receive a curated list of R&D-relevant resources on agentic AI after the event.

Can’t attend live? No worries, we will send the recording to all registrants.

08/13/2025

The shift from sequential to concurrent materials design is transforming R&D. In our latest blog, we explore how three critical AI capabilities are enabling this leap: advanced optimization, generative AI, and agentic AI systems.

Companies like Dow, 3M, Apple, and Tesla are already leveraging this approach to co-optimize materials alongside product design, processing conditions, and manufacturing from the initial concept phase, achieving faster development cycles and globally optimized solutions.

This isn't gradual change. It's a fundamental paradigm shift that allows R&D teams to create superior, differentiated products.

https://www.enthought.com/blog/concurrent-materials-design-accelerated-by-ai/

07/09/2025

Great article about Unilever's approach to AI in R&D - "Research and Development (R&D) has always been our engine of progress. But now, that engine is being transformed by AI."

Key highlights (and pro tip - you definitely do not need 100 years of data to leverage AI in R&D!):

💡 The questions being asked today have become more complex, requiring new ways of doing science. That’s where AI comes in.
💡The companies that thrive today will be the ones that know how to adapt, how to learn, and how to build on what they already know.
💡 AI can be a catalyst for transformation, by harnessing untapped research, product development, and consumer insights.
💡 AI helps scientists unlock proprietary knowledge that was once siloed, scattered across teams, or locked in an archive.
💡 Agentic AI systems are not about replacing scientists with algorithms but creating environments for them to ask better questions, explore more possibilities, and unlock insights from data.
💡AI rewards companies that see technology not as a threat to tradition, but as a way to reimagine it.

Full article: https://www.fastcompany.com/91359412/legacy-companies-with-rich-data-are-transformed-by-ai

The most successful companies will use AI to adapt, learn, and build on what they already know.

06/30/2025

AI is poised to profoundly transform scientific R&D in the next decade. In his new article on Forbes.com, Enthought COO Michael Connell highlights his top predictions in the field, from why predictive AI will overtake generative AI in value to what new R&D roles will emerge and more. Do you agree? https://www.forbes.com/councils/forbestechcouncil/2025/06/30/6-predictions-how-ai-will-transform-scientific-rd-in-the-next-decade/

Given the variability between labs and the unique nature of R&D work, custom, niche AI tools are going to become much more prevalent.

06/19/2025

We couldn't agree more with this powerful sentiment from Sam Altman: "AI will contribute to the world in many ways, but the gains to quality of life from AI driving faster scientific progress and increased productivity will be enormous; the future can be vastly better than the present."

The single greatest catalyst for this future isn't just a new discovery, but a new way of discovering.

AI is poised to fundamentally reshape scientific R&D. For labs and research organizations, this means:

🔬 Accelerating discovery cycles, now potentially by orders of magnitude.
📊 Uncovering novel insights from complex, multimodal data.
💡 Freeing your brilliant researchers from tedious tasks to focus on what matters most—breakthrough thinking.

Leveraging AI and advanced technologies in R&D is what we do at Enthought.

What's your top bottleneck in your research process you believe AI could solve?

[Sam Altman's recent blog: https://hubs.la/Q03s69hd0]

03/15/2025

🤖🔬 The era of the AI Co-Scientist is here. How is your organization preparing? In this month's article "The Emergence of the AI Co-Scientist," we discuss the latest huge advancement poised to truly transform research and product development. We highly recommend you read this one 👉 https://hubs.la/Q03b-0rn0

The era of the AI Co-Scientist is here. How is your organization preparing?

02/17/2025

👀 In the News | What Enthought has coined as "AI supermodels", the next generation Materials Informatics, is transforming materials discovery. Editor-in-Chief Brian K. Buntz of R&D Magazine shares his takeaways on the subject from his conversation with Enthought COO Michael Connell in new article 👉 Early tests show ‘AI supermodels’ can speed up materials discovery by 100x (or more) with minimal data: https://www.rdworldonline.com/early-tests-show-ai-supermodels-can-speed-up-materials-discovery-by-100x-or-more-with-minimal-data/

Despite all of the bluster surrounding AI’s transformative promise, some R&D projects—especially in areas like battery materials development and drug discovery—face significant bottlenecks when relying on these tools, often requiring days and sometimes weeks or even months of GPU processing ti...

02/10/2025

The R&D digital transformation (DX) landscape is evolving once again—driven by the rise of generative AI and now AI agents—and budgets need to keep pace. Enthought Chief Operating Officer Michael Connell shares his thoughts on how R&D leaders should think about their DX budgets today as pressure increases to deliver measurable outcomes. Full article 👉 https://bit.ly/3CEd7U2

Key Takeaways:

➡️ Recalibrate ROI expectations between digital enhancements and digital transformation
➡️ Have a centralized authority who owns the R&D digital transformation budget vs. distributing among siloed business units focused on short-term outcomes
➡️ Establish clear decision-making mechanisms for budget allocation

Learn how companies are rethinking their digital transformation budgets for 2025 and realigning expectations to effectively leverage technology for business growth.