They may have been slower to bring AI tools to market than some start-ups, but the big software companies have large R&D budgets, sizable workforces and masses of data at their disposal. Here, we get a glimpse from four senior executives on how they see AI and what might be in the pipeline at their companies
Jeff Kinder // Autodesk
EVP of product development and manufacturing solutions
I believe we’ll see AI automate mundane tasks more and more across all industries, but certainly in design and manufacturing. In the next year, I think we’ll see AI surface even more in design to accelerate the creative process.
I believe we’ll see a fork in the AI road. The fascinating and novel capabilities that we’ve become accustomed to thinking about as defining AI, such as natural language prompts yielding fantastic images, essays and code, will continue to advance. At the same time, very practical, somewhat mundane AI capabilities will emerge. And these advancements will save us immense amounts of time. Soon, busy-work tasks that used to take hours or even days will be completed with a simple click of a button. And we’ll get that time back to do the creative work that humans excel at, while the computer focuses on computing.
With disconnected, disparate products, organisations can only achieve incremental productivity gains. To see breakthrough productivity gains, data must fl ow seamlessly and be connected end to end. The productivity increases will be a welcome accelerant in and of themselves, but they’re also the fuel for building more AIpowered automation tools.
Manish Kumar // Dassault Systèmes
CEO Solidworks, Dassault Systèmes
With 95% of companies anticipating that AI will improve product development, it’s increasingly important for organisations to ensure their AI systems are built on a foundation grounded in reliable, high-quality data. I believe 2025 will be crucial in laying a data-driven foundation that allows AI tools to thrive.
Many organisations lack a centralised platform to collect and manage the data that is vital for training AI models, which may introduce potential risks, such as inaccuracies in automated designs, lack of transparency in decision-making and potential security vulnerabilities that require careful management. Without a clear picture of all the data at your disposal, AI models also won’t function to their highest capability. This involves know-how in addition to hard knowledge. Key learnings are critical to input into AI models to complement facts and ensure that users do not make the same mistakes twice.
AI will be the determining factor that ultimately streamlines and optimises design capabilities, but 2025 can be considered a bridging year, for ensuring that AI models have all the data in place to ensure organisations are maximising their potential.
Todd Tuthill // Siemens Digital Industries Software
VP of aerospace and defense
Using natural language to ask questions and interact with software allows new users to learn and use complex software more quickly and with less need for expert guidance. At the same time, experienced users can seamlessly automate workflows and speed up tasks. However, while industrial AI chatbots represent an important first step on the path of bringing AI into professional software, they should not be mistaken for the end goal. In the increasingly complex and digitally integrated world of modern design and manufacturing, AI is uniquely positioned to connect people and technology in a way that plays to the strengths of both with AI moving many of the burdens of professional software away from the user. Over the course of the coming months and years, AI will not just be a novelty in industry, but a critical technology that will upend the way that products are designed, manufactured and interacted with.
Companies that fail to adopt AI will find themselves unable to keep up in a fast-paced world where competitors have continued their digital transformation maturity journey – a journey that will lead to an autonomous, intuitive and integrated design process far surpassing anything that exists today.
Jon Hirschtick // PTC
CEO, PTC Onshape, speaking to Engineering.com
I think AI is critical. I think our users must feel like product developers did when plastics or carbon fibre came along. It’s not just a better way of doing things; it’s a whole new set of tools that make you redefine problems.
AI allows you to approach problems differently, and so the baseline is important, not only for study but also for releasing products. Just like with the first plastic product, you can’t know what it’s really like until you use it. We need to build reps, to understand how to deliver and leverage the cloud-native solutions of Onshape.
Our system captures every single action as a transaction. If you drill a hole, undo it, or modify a feature, that’s all tracked. We have more data than any other system about a user’s activity, so we don’t need to go out and collect data manually. This gives us a huge advantage in training AI applications.
In the future, users might even be able to combine data from their channels, emails, and other sources, and create a composite picture of what’s happening. We’re working on ways to give more value without relying on manual collection.
This article first appeared in DEVELOP3D Magazine
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