For CIOs, generative AI is quickly becoming a mission-critical collaborator due to its ability to augment human ingenuity and innovation.
More companies across Asia Pacific are embarking on their AI journeys, with a recent Autodesk report finding that 68% of the region’s construction businesses have plans to use the technology.
Autodesk AI, in its Design and Make Platform, provides intelligent assistance and generative capabilities that allow customers to imagine and explore freely while producing precise, accurate, and innovative results.
How are advances in AI/ML impacting design processes and the role of the CIO? DigiconAsia discusses the developments and changes with Prakash Kota, SVP & CIO, Autodesk.
How is AI/ML fundamentally transforming design processes and outcomes today?
Prakash Kota (PK): Building design is traditionally a time-consuming and manually intensive process.
Advances in AI, especially in generative AI technology, have accelerated a revamp of the modern design and make process. People and AI can form a symbiotic relationship: People give AI the data it needs to create, and in turn, generative AI promotes new ideas and innovation, empowering architects with data-backed insights to make more informed decisions throughout the design process.
For example, AI is capable of analyzing vast amounts of data at scale to simulate a building’s performance throughout its anticipated lifecycle, helping architects to assess the feasibility of their design and to identify potential areas for improvement.
This can help teams more effectively adjust their designs early in the construction process, facilitating the creation of buildings that more closely meet the needs of its users, create less negative impact on the community and environment, or are less expensive to operate. It also leads to shorter project completion times, a factor essential for rapidly growing economies across Asia Pacific such as Singapore where large public sector projects currently represent more than half of construction demand in 2024.
At Autodesk, we envision AI serving as an assistant in the design process, with designers retaining their role as decision-makers, controlling the creative process and ultimately making the final call. The integration of AI-enabled capabilities into the design process does not mean people will no longer be required; instead, it empowers them to focus on better outcomes.
Similar to what Google Gemini or ChatGPT has been doing for creative professionals, the generative potential of AI can empower architects with better ideation capabilities. Generative AI solutions can rapidly develop and recommend designs within a set of pre-determined parameters, helping architectural teams refine or think about design possibilities in ways that they may not have previously considered. Beyond optimizing design, AI can also be used to automate repetitive tasks to allow for a focus on creative aspects of construction.
It seems that AI (especially generative AI) could not have taken off without the pervasiveness of the cloud, and the combination of AI and cloud technologies has got a significant impact on productivity and innovation. What are some examples where you have seen this happening?
PK: Cloud technologies are often described as an enabler for AI, providing the infrastructure and computing resources necessary for its development and deployment. A fairly recent example was the Singapore government’s collaboration with Google Cloud to launch the Artificial Intelligence Government Cloud Cluster (AGCC). This was aimed at allowing local government agencies to take advantage of Google Cloud’s enterprise-grade AI technology stack to quickly build and deploy AI applications for public sector use.
The successful combination of AI and cloud technologies is also observed internally at Autodesk. Our suite of AI technologies, Autodesk AI, is powered by our Design and Make platform, a cloud-connected software platform that integrates design and manufacturing workflows as well as cloud resources to support AI functionalities.
This has given rise to multiple use cases at Autodesk, including the recently announced Project Bernini, an experimental research effort focused on using generative AI to generate functional 3D shapes based on a variety of inputs including 2D images, text, voxels and point clouds.
The Bernini model was trained on ten million diverse 3D shapes, enabling it to generate models that reflect the purpose that the designer has in mind. Take a water pitcher for example. While many other 3D generative models may produce shapes that merely look like a pitcher, those generated by Bernini are hollow in the middle, being designed to actually hold water – as any real-world pitcher would need to do.
As a CIO yourself, how do you perceive the changing role of the CIO in an increasingly AI-driven business world?
PK: The role of the CIO is registering a significant shift amid the rise of AI. While CIOs traditionally focused on managing IT infrastructure and operations, they play a strategic role today that bridges the gap between technology and business.
Where AI is concerned, CIOs are not only responsible for AI adoption, but also implementing these technologies the right way. This involves accurately identifying how AI can benefit their organizations and driving its adoption in relevant areas of the business with the right training. This trend will make AI fluency increasingly important for CIOs, as well as the ability to understand the capabilities and limitations of AI tools, and how to integrate them effectively into organizational systems.
With AI workflows intersecting with areas such as data science, cloud technologies, and cybersecurity, collaboration is also set to become key to the CIO role. They will need to work closely with business leaders across different departments to either identify how GenAI can support workflows, or where it can add value. This also makes CIOs indispensable to technology providers, serving as the conduit that link solutions to customers in design and make industries.
The exponential growth of multi-modal AI models is on the horizon. What does this mean for CIOs, and how can they capitalize on the emerging opportunities?
PK: The rise of multi-modal AI models represents a transformative shift in how organizations can leverage data and AI technologies. Multi-modal AI models empower CIOs to more easily tackle complex problems. The ability to combine various data types – from image, text, audio, or numericals – enables multi-modal AI models to generate more detailed and customized insights, facilitating better decision-making across the organization.
An example from a design perspective includes multi-modal AI algorithms that are capable of ingesting textual data on areas on regulations, climate, or user preferences, and combining it with analysis of images of the project site. This provides architectural teams with far richer insights than what single-modal AI provides. For CIOs, this means preparing their IT infrastructure to support these advancements, and also leading their organizations in adopting, integrating, and innovating with multi-modal AI.
CIOs can focus on the following areas to more effectively realize the multi-modal AI opportunity:
- Having a great data management strategy and infrastructure: Data is the fuel that powers AI, and multi-model AI models are no different, working best when it has access to high-quality data. The most successful companies will be those that invest in adequate infrastructure to effectively collect, store, and analyze quality data, and implement the right strategies to ensure that this data is readily available, secure, and well-integrated across the organization.
- Building a talent pipeline: A successful multi-modal AI strategy relies on the ability of CIOs to hire or cultivate employees with the right skill sets. This could include data scientists, AI specialists, and domain experts, all collaborating to build effective AI solutions.
- Instilling a culture of experimentation: AI is a rapidly evolving technology with new processes, and algorithms are constantly being created. Instilling and encouraging a culture of implementation allows new possibilities to be regularly explored across the organization, giving rise to new use cases to improve productivity and business outcomes.
