AI adoption success depends on trust, communication, and change management—not just technology. Customer Success teams must focus on adoption metrics and organizational readiness to make AI transformations truly work.
Her Story
About Payal
Payal Dedhia serves as a Customer Experience and AI Adoption Specialist at Apple in New York City, a role she has held for approximately one year. In this position, she assists business customers with Apple products and AI agent implementations, drawing on her expertise as an AI generalist. With a decade in technology and 27 years of overall professional experience, Dedhia previously worked at a SaaS company and Data Engineer Academy. Her career began in the film industry in Bollywood, where she produced ad films and managed teams of over 750 people. She also maintains a side practice as a consultant and business coach focused on AI adoption and enablement for over 20 years. Dedhia holds three master's degrees: an MBA in Management and Marketing Analytics, another master's in Management and Marketing Analytics, and a master's in Economics. She attributes her success to her ability to optimize processes and anticipate improvements, creating compound effects over time. Dedhia is a recipient of Marquee's Who's Who recognition and multiple awards to her films, and she belongs to the American Marketing Association along with various film and technology associations. She serves on the board of Unity for Equality, supporting women's financial education, and participates with MAD, an India-based initiative for rural student upliftment and education. Her values center on freedom, family, and continuous learning, as evidenced by her continuous learning in an AI and the Art and Science of Coaching by Erickson ICF (PCC Pathway track).
Her Interview
Ten minutes with Payal
01What do you attribute your success to?
I attribute my success to the skill I've developed over the years to look around the corners. I optimize processes and my mind is constantly thinking what I can do better, how I can save time, what I can do better, how I can make it more convenient. It's very small, but when you amount it, it becomes really big - the compound effect.
02What advice would you give to young women entering your industry?
Give yourself the permission to walk away, no matter what. Be a lifelong learner because every technology changes - first Java, then SQL, Python, now AI. Don't be averse to learning something new; at least put an effort to learn it before passing a comment.
03What are the biggest challenges or opportunities in your field right now?
The biggest challenge is change management because society is divided between those embracing AI and those averse to it. Opportunities are human opportunities - AI handles mundane tasks freeing time for family, friends, and personal activities like pickleball.
04What values are most important to you in your work and personal life?
Freedom is super important to me. Family and learning - I have to learn, I have to grow. I'm taking another AI accelerator program and Art and Science of Coaching by ICF.
Her Content Hub
Articles by Payal
Leading Through the AI Shift
Why AI adoption succeeds or fails depends on customer success, not technology.
By Payal Dedhia
Every AI adoption conversation eventually arrives at the same question: whose job is it to actually make this work? Not buy the tool. Not announce the rollout. Make it work for real people, inside a real business. That job almost always lands on Customer Success.
Companies treat AI adoption like a technical rollout—pick the tool, train the team, measure usage. It isn't technical. It's the customer who doesn't trust a chatbot with their account. It's the employee quietly avoiding a new workflow because nobody explained why it matters. It's a leader who greenlights an initiative without asking who it will actually hit.
I've worked at this intersection across enterprise advertising, EdTech, retail technology, and AI startups, and the pattern never changes: the technology is rarely the hard part. Trust is. Communication is. Change management is.
The Challenges
Credit. The people translating what AI can do into what a customer or an executive will actually accept are doing the real work of a transformation. That work is often invisible on an org chart—credited to whoever built the technical thing, not whoever made it land.
Measurement. I drove zero churn across a 200+ client portfolio and a significant NPS jump at a previous company by treating adoption, not deployment, as the metric that counted. Most organizations still grade AI success by technical benchmarks that have nothing to do with whether anyone actually trusts the thing.
Pace. Leaders want the outcomes of transformation without doing the organizational work transformation demands. Whoever sits closest to the customer or the team absorbs that gap first—usually without being asked if they're ready to.
None of this gets fixed by better prompting or a faster rollout schedule.
The Advice
Own the translation work instead of apologizing for it. Explaining a technical shift in terms a customer or executive can act on isn't a soft skill—it's the skill the whole rollout depends on.
Measure what's real. Adoption, trust, retention. Not activity logs.
Find the blind spot before the company pays for it. Every AI rollout has one—an assumption nobody stress-tested, a team nobody consulted.
The businesses that win this decade won't be the ones that deploy AI fastest. They'll be the ones that make it trustworthy enough for people to actually use.
Join Influential Women and start making an impact. Register now.