Tom Gruber
Most boards now own an AI strategy on paper. Far fewer can defend, in front of customers, regulators or their own workforce, the design choices behind it. The gap between deploying AI and deploying it in a way that earns trust, holds up to scrutiny, and actually augments the people using it is where serious organisations are getting stuck.
Tom Gruber co-founded Siri and originated the concept of Humanistic AI, helping leadership teams design AI systems that augment people rather than replace them.
Full Profile
Why organisations work with Tom Gruber
- He shipped the first mainstream intelligent assistant. When he speaks about what AI deployment actually requires inside a product organisation, it is from the inside of a system Apple now runs across its entire device base.
- He authored the foundational definition of an ontology in computer science. Boards wrestling with AI governance, knowledge representation and explainability are talking to the person whose 1993 paper their technical teams still cite.
- His Humanistic AI framework gives leadership a usable language for AI design choices. It moves the conversation from “should we use AI” to “what does this system do for the human using it”, which is the question regulators and employees are now asking.
- He chooses his advisory portfolio around AI applied to assistive neurotech, mental health and clinical accuracy. The examples he brings to a keynote are concrete deployments, not hypotheticals.
- He is one of very few speakers who can credibly walk a room from ontology engineering to product design to ethics in a single talk, without losing either the technical audience or the executive one.
Biography highlights
- Co-founder, CTO and head of design of Siri Inc., acquired by Apple in 2010.
- Led Siri’s Advanced Development Group at Apple for eight years following the acquisition.
- Author of the foundational 1993 paper defining ontology in AI, the highest-cited article in the history of the International Journal of Human-Computer Studies.
- Main-stage TED 2017 speaker on Humanistic AI.
- Co-founder and CTO of LifeScore, an adaptive AI music company backed by Octopus Ventures.
- Advisor to the Ocean Plastics Leadership Network on organisational intelligence and technology.
Biography
Siri began as a research project, became a startup, and was acquired by Apple in 2010, the same year it launched. Tom Gruber was its co-founder, CTO and head of design. The product now runs across Apple’s device base and processes more than a billion interactions a day. Most of what users now expect from a voice assistant was decided inside the small team he helped lead.
Before Siri, the foundation. In 1993, working at Stanford’s Knowledge Systems Laboratory, Gruber published the paper that gave AI its working definition of an ontology: “an explicit specification of a conceptualization”. It became the highest-cited article in the history of the journal it appeared in, and it remains the reference point for anyone building systems where machines have to share knowledge cleanly. The shipping product and the citation history are connected. Siri worked because the underlying representation was right.
After eight years leading Apple’s Advanced Development Group for Siri, Gruber stepped out to focus on what he calls Humanistic AI. The argument, set out in his 2017 TED talk, is that AI design is a choice between automation that competes with people and augmentation that collaborates with them. He puts the framework to work as co-founder and CTO of LifeScore, an adaptive music company, and as advisor to AI ventures in assistive neurotechnology, mental health, and clinical decision support.
The Humanistic AI lens is what leadership teams find most useful from him. It reframes AI deployment as a design decision with named consequences for customers, employees and society, rather than a procurement decision about which model to license. For boards approving AI strategy and CEOs explaining it, that reframing is doing work no other AI keynote does.
Key speaking topics
- Humanistic AI and human-centred design
- AI governance, ethics and trust
- Intelligent assistants and conversational AI
- Ontology engineering and knowledge representation
- AI in assistive technology and healthcare
- AI for collective intelligence and ocean conservation
- Building AI products from research to scale
Ideal for
- Boards and CEOs setting AI policy and accountability
- Chief Technology Officers and Chief AI Officers shaping enterprise AI deployment
- Heads of product and design building AI into customer-facing systems
- Healthcare, financial services and public-sector leaders deploying AI in high-stakes contexts
Audience outcomes
- A working definition of Humanistic AI that distinguishes augmentation from automation in their own operating context
- A clearer framework for evaluating AI design choices against customer, employee and societal impact
- Concrete reference points from Siri and from current AI deployments in healthcare, assistive tech and creative industries
- A language for leadership conversations about AI ethics that goes beyond compliance and into product design
- Recognition of where their own AI roadmap is making automation choices it should be making augmentation choices
Talks
A framing of AI design as a choice between competing with humans and collaborating with them, illustrated with current deployments from Gruber’s advisory portfolio.
Key takeaways:
- The design distinction between automation and augmentation, and what each implies for product, workforce and customer.
- Examples of Humanistic AI in assistive neurotech, mental health and clinical decision support.
- A framework for leadership teams to test whether their AI strategy is augmenting their people or hollowing them out.
The story of why top venture firms backed Siri during a financial crisis, distilled into practical lessons for AI ventures and corporate innovation teams.
Key takeaways:
- Four decision points from Siri’s trajectory that translate to any AI product build.
- What investors actually evaluate when AI is the core thesis.
- The role of design and ontology in making an AI product defensible at scale.
A direct contrast between AI misuse by major platforms and AI applied to healthcare, mental health, assistive care and pandemic response.
Key takeaways:
- Where the real risks of AI sit, beyond the popular framing.
- Specific AI applications producing measurable human benefit today.
- What governance looks like when it is treated as a design problem, not a legal one.