Tom Acland serves as the CEO of Dassault Systemes 3DEXCITE, where he drives innovation through virtual commercial twins for industrial companies. With nearly 22 years of experience, he has held leadership roles at Microsoft, Publicis Groupe, and Bosch, blending digital marketing and product development expertise. Tom began his career in a DotCom startup and was CTO at Razorfish in Germany, where he pioneered initiatives for Audi and Novartis. He Co-Founded COBI, an IoT startup, and now leads a global team at 3DEXCITE.

AI plays a pivotal role in reducing the time to-market for new products by leveraging various innovative techniques. Market analysis covers a vast area that unravels key trends and consumer preferences, such that it produces tailored products. Through design automation, it generates rapid iterations, predictive analytics lets it predict potential issues that can affect the smooth workflow in delivering time-to-market pace issues. All of these increments in supply chain management and quality assurance keep up the pace in making things quicker and ensuring that the product reaches the market on time.

In an exclusive interview with SiliconIndia, Tom Acland, CEO of 3DEXCITE at Dassault Systemes, emphasizes the transformative impact of AI on product design and development. He notes that AI-driven technologies are revolutionizing traditional processes, allowing organizations to optimize workflows, improve efficiency, and promote innovation across various industries.

How is AI changing the nature of conventional design development and sup-porting improvements in organizational processes?

AI is revolutionizing the conventional design development process and transforming organizational workflows. Its application spans the entire design lifecycle, from initial ideation to the final product interaction, driving significant improvements. One of the key ways AI is enhancing design is by narrowing the focus during complex problem-solving. In scenarios where multiple approaches may be viable, AI efficiently explores the solution space, identifying the most promising candidates for further validation. This allows organizations to streamline the process, reducing time spent on preliminary testing and focusing efforts on rigorously evaluating the best potential solutions using traditional methods, resulting in more precise and reliable outcomes.

Additionally, AI is expanding access to advanced methods and tools, particularly through techniques such as modeling and simulation (ModSim). By integrating modeling and simulation into a unified workflow, ModSim enables designers to simultaneously design and test concepts without needing separate specialists for each function. This integration allows for faster iteration and validation of designs, improving efficiency and performance. However, The rapid evolution of AI tools has created tool chain volatility, with frequent new approaches emerging. To address this challenge, organizations are increasingly partnering with specialists to manage backend complexities, ensuring optimal application of AI technologies while allowing internal teams to focus on their core objectives.

AI plays a crucial role in tailoring the presentation of product features and benefits to meet the diverse needs of different markets

What current uses of AI tools/technologies in product design and proto typing methodologies that companies are using or exploring?

AI tools are revolutionizing product design and prototyping by streamlining processes and fostering innovation. Currently, AI helps companies enhance efficiency by identifying pre-existing solutions, reducing the need for custom designs, and lowering production costs. It also aids designers in evaluating sustainability and ensuring supply chain reliability, helping organizations prepare for scalable manufacturing. Emerging AI technologies are further transforming early-stage development, allowing for rapid concept creation and more efficient prototyping. Techniques like AI-driven spatial computing bridge the gap between physical prototypes and virtual models, enhancing real-world validation and reducing time to market. Looking ahead, AI is expected to be integrated directly into products, enabling them to interact with their environments and make autonomous decisions. This shift will require engineers to develop adaptive systems driven by AI, as advances in AI-capable hardware push the boundaries of intelligent product design.

How has AI changed the time-to-market of new products in other industries?


AI has significantly accelerated the time to market for new products by enhancing processes involved in commercial innovation, particularly in go-to-market strategies. From a product localization perspective, AI plays a crucial role in tailoring the presentation of product features and benefits to meet the diverse needs of different markets. Localization is vital for companies aiming to export products, as specific features may hold varying value depending on the market; for instance, heated seats may be considered essential in Sweden but a luxury in Milan. Historically, localization has been a manual and time-consuming process, requiring extensive research to understand market-specific needs. However, AI has transformed this by integrating the specificity and accuracy of product information with general market knowledge, automating much of the contextualization work and enabling companies to create market-specific narratives more efficiently.

Additionally, AI facilitates hyper-personalization, allowing products to be refined to meet individual consumer needs based on personal preferences and situational demands. This not only enhances product relevance but also delivers greater value to consumers while optimizing resource use, ultimately supporting sustainability by balancing customer satisfaction with reduced environmental impact and establishing AI as an essential tool for both commercial and environmental innovation.

What are the ethical considerations organizations need to address while deploying AI technologies in their product development initiatives?

Organizations utilizing AI technologies in product development must address critical ethical considerations to ensure responsible use. A significant concern is bias, they need to ensure that the assumptions underlying AI-generated suggestions are representative and do not inadvertently disadvantage specific groups. This necessitates continuous assessment and refinement of algorithms and data sets to promote inclusivity. Protecting intellectual property (IP) is also vital, as safeguarding innovations fosters a vibrant knowledge based economy. Establishing robust frameworks for IP security encourages investment in innovation. Furthermore, organizations must differentiate between truth and narrative, as AI interfaces can skew users perceptions of information. Transparency and access to factual information are essential for mitigating the impact of misleading narratives. By selecting fairness, safeguarding IP, and confirming information integrity, organizations can foster informed discussions and contribute positively to society, thereby promoting a culture of responsible innovation.

In what way can designers ensure that AI driven products are both user-friendly and ethically responsible, especially in terms of data privacy and bias?

Designers are necessary in making AI-driven products both user-friendly and ethically accountable, particularly regarding data privacy and bias. Their roles go beyond basic product design to encompass process and systems design, underscoring the importance of tackling fundamental issues rather than just concealing them with AI improvements. A critical aspect of this responsibility is the governance of training data. By ensuring that training sets are well-represented and less biased, designers can enhance the accuracy and reliability of AI models. Implementing guardrails and prompt engineering aligned with organizational values also helps communicate the purpose behind AI functionalities.

How is integration of artificial intelligence in product development reshaping traditional methodologies and enhancing innovation across various industries, particularly if you say areas like healthcare, automotive, and retail?

The integration of artificial intelligence (AI) into product development processes marks a significant shift toward democratization and accessibility across various industries. Natural language interfaces are becoming essential tools, particularly in the automotive sector, where designers can create user-centric experiences. For instance, vehicles could be programmed to adapt their functions based on environmental conditions—ensuring cleanliness during rain or adjusting interior temperatures on hot days. This demonstrates how AI can enhance customer interactions, making them more intuitive and personalized.

In manufacturing, the application of computer vision technology significantly improves efficiency during late-stage validation, traditionally a time-consuming process. By enabling real-time issue identification, such as detecting corrosion or misalignment, manufacturers can expedite diagnostics and proactively address defects, ultimately streamlining workflows and enhancing product quality. In healthcare, computer vision aids in rapid diagnosis, informing clinical decision-making and improving patient outcomes. Retail also benefits from AI-driven insights that transform customer service; leveraging data analytics allows retailers to better understand consumer behavior and preferences, enhancing user experience. Through the thoughtful integration of AI technologies, industries can drive innovation and create more responsive, user centric solutions.

Final Note

As industries increasingly adopt AI, prioritizing ethical practices and user-centered design becomes essential for building trust and promoting sustainable innovation. Ultimately, effectively incorporating AI into product development not only increases functionality and efficiency but also fosters a more equitable and thoughtful approach to addressing the diverse needs of consumers.