AI Magazine speaks with AI business leader Sophia Velastegui as she offers advice for businesses seeking to advance their AI use cases responsibly
As businesses continue to power ahead with their AI investments, they seek to also improve their strategies to achieve real growth – something which Sophia Velastegui knows plenty about.
In this exclusive interview with AI Magazine, Sophia speaks about her work surrounding AI as a woman within the sector, in addition to how businesses can best overcome the technical challenges of AI.
Sophia is an AI business leader, consultant and board director with more than 20 years of experience across the AI and technology industries. She has worked at a range of big tech corporations, including Google, Apple and Microsoft as a Chief AI Officer. Her work now focuses on helping organisations harness AI to its full potential for innovative business growth.
Please introduce yourself and tell us about your background in AI.
My love of AI started at Apple, working on introducing new products to consumers, including the first iPad. I noticed that a single iPad could host unlimited apps and the best-performing apps leveraging AI. So I moved to the team that supported Apple’s AI systems and products – from Apple Maps to CarPlay.
I leaned into AI products exclusively in my next role at Google’s Nest, where we reimagined unloved home products and turned them into smart, responsive tech. My work focused on infusing AI into everyday products like thermostats, smoke detectors and camera systems to provide comfort and safety for users.
Thanks to this experience, Microsoft recruited me to be part of the “Hit Refresh” culture and tech transformation from a hardware and software dinosaur into an industry-leading AI company. As General Manager of AI Products and Search, my team was responsible for creating the new AI features to enhance existing Microsoft products like Microsoft Search and Office. Later, I was promoted to Chief AI Tech Officer in the business applications group, where we introduced the first enterprise Gen AI Copilot products.
Most recently, I served as the Chief Product Officer at Aptiv, leading the most advanced applied AI system ecosystem in the self-driving car business.
Tell us about the work you are currently doing in AI.
Today, I’m advising Fortune 500 companies on planning and executing right-sized and scalable AI business strategies. I’m also lending my expertise as an AI advisor for the National Science Foundation.
My clients are feeling the pressure to do something – anything – with AI so they aren’t left behind. But I help them strategically plan to use AI to enhance their current model – whether that’s solving for efficiency to cut costs or becoming more innovative to drive revenue.
The market is saturated with AI experts, but very few have leveraged both traditional and Gen AI to successfully create significant business value. So I have the chance to share my experiences from actually helping to build and launch AI businesses and offer a unique perspective on how companies can get ahead of their competition.
What current trends are you seeing in AI that you are excited by?
Where do I start? Multimodal AI is a trend that is here to stay. We’re on the cusp of AI being able to incorporate disparate pieces of information and produce more targeted insights and capabilities.
Think about OpenAI: They started with ChatGPT and text interactions and then rolled out Dall-E to generate images based on words. Then comes Sora, with generated video, and Whisper, creating generated audio.
Each type of data is distinct, but combining them will unlock a whole new world of creativity. And with the widespread adoption of multimodal AI, we’ll start to see historically siloed enterprise data be mined for even deeper insights.
How can businesses best overcome AI-associated challenges? What advice would you offer?
Understand that AI strategy = business strategy: Companies can best leverage AI by ensuring it’s aligned to the core businesses and deployed where it can create the biggest impact, because the upfront investment is significant. Think about whether AI can be incorporated into existing mission-critical products or services, as opposed to developing something entirely from scratch.
Avoid pilot purgatory: Too often, I see companies hyper-focused on AI without the right strategy behind the action. Everyone wants to say they’re using AI, but without targeting value creation, the danger is spinning the company’s wheels and ending up in pilot purgatory with a lot of money wasted.
Develop the guiding framework and ethics: Empower a cross-functional team to develop a governing AI framework. Those guardrails must be in place to ensure that AI is being used ethically and proprietary data is being protected.
What are some of the opportunities or challenges you see as a woman working within the AI sector?
The opportunities are immense in AI right now and I encourage women to go after them.
HERE’S WHY:
- AI offers a path to a high-growth career while also making a huge impact on the future.
- Women at the table, using their voices and sharing their perspectives, will help to address issues of bias that are embedded in the technology.
- We need more women leaders who understand the value of AI and how it will shape every industry.
- Gen Z are the most tech savvy generation to date, so they are entering the workforce already primed to jump into the new AI ecosystem, regardless of role. I foresee Gen Z pushing the rest of us to think bigger and adopting AI even more broadly to solve business challenges.
Gen AI increased accessibility across the board, not just for technologists. But right now is the smallest gap of understanding between those who “get” AI and those who don’t. So the time is right if you’ve been thinking about exploring AI to advance your career or to make a shift into the AI sector. I look forward to seeing even more women making waves in our industry.
Moving forward, how can businesses best leverage AI in a way that is responsible?
Definitely implement the guiding framework and ethics, as I mentioned before. Businesses also need a feedback loop to understand how AI is actually working day-to-day with input from their teams. By sharing learnings across projects and divisions, it helps to minimise challenges and allow for flexibility before it’s too late.
I’d also recommend putting in place a cross-functional “AI council” that’s responsible for providing the framework, understanding regulations, addressing bias, enforcing ethical standards, adopting lessons learned and aligning with the core business strategy.
AI doesn’t operate in a vacuum. It requires a full ecosystem and diverse teams to support and sustain a successful deployment – no matter your line of business.
