Keynote Speaker
4x C-Suite & Amazon Exec; World’s 1st Chief AI Officer; 10 Patents; Best-Selling Author and Forbes Writer; “Top 100 AI Thought Leaders”; “50 Most Powerful Women in Tech”; Harvard Fellow
Audiences can expect an energetic, insight-rich experience grounded in real-world AI leadership. As the world’s first Chief AI Officer, a 4x C-Suite exec, and holder of 10 patents, Sol delivers practical, future-focused strategies that help leaders adopt AI responsibly, unlock ROI, and empower teams to thrive in a tech-driven world.
Sol Rashidi's speaking fee: $40K - $70K
As the world’s 1st Chief AI Officer for enterprise (2016), Sol has 10 patents and is the best-selling author of Your AI Survival Guide (‘Top 50 AI’ books). A 3x TEDx speaker with 1M+ views, and voted FORBES “AI Maverick & Visionary of the 21st Century,” and FORBES “Top 5 Leaders Taking AI to Everyone”, Sol is a former 4x C-Suite exec for Fortune 100 companies and a former Amazon tech exec. Sol is the inventor of The Human Amplification Index™ (a new way to measure ROI for AI and Automation to determine how well companies are strengthening their business and workforce through AI) and Intellectual Atrophy™ education to ensure we outsource tasks and not critical thinking in the age of AI. Sol played a pivotal role in developing and launching IBM’s Watson in 2011 and now has over 200+ deployments under her belt. As both a practitioner and an executive, she has earned accolades like “50 Most Powerful Women in Tech,” “Top 100 AI Thought Leaders,” and “Top 100 Data & Analytics Leaders.” Sol sits in the intersection of top-tier leadership in AI, technology, and corporate strategy while bridging innovation with business impact. She serves as a public educator and thought leader, shaping conversations about AI, business transformation, and preparation of the future workforce. Her mission is to ensure AI and Automation amplify the workforce and do not displace it.
Geared for Non-Technologists who want to make sense of the AI world and what it entails, this conversation gets past the ‘Art of the Possible’ and into the ‘World of the Practical’. A majority of us aren’t technologists, so it’s important to understand what all this means today, for the future, and how to best be prepared for it personally and professionally. It also discusses the hype, the marketing, what is fact vs. fiction, and how to tell the difference.
With the advent of AI and with nearly 86% of organizations investing in AI-based capabilities, it’s been proven that AI is not a fad or a trend that will go away. However, what we can’t measure are the economic and moral impacts AI will have on our society. Like parents, who are the caretakers of children, their responsibilities are to teach children right from wrong and to embed a moral compass in each of us. Similarly, WE as humans are the caretakers of AI, also teaching it right from wrong, yet we’re at a crossroads with a moral compass because of the biases, poor practices, falsification, and misinformation we’re helping it propagate. I will share a personal story of how ‘fake news’ almost ruined my 20+ career and how I caught it, and how to embed safer and responsible practices for AI.
While many companies strive to be innovative, nearly 76% of all innovation projects fail, and nearly 92% fall short of expected results. This conversation focuses on how to avoid the pitfalls and quicksand of innovation and why BUSINESS VALUE is not the metric of choice when choosing your innovation projects. It also discusses how to make sense of the new world of CXO’s where the boundaries of technology have expanded past the CIO. How should one think through the division of labor, motivating a workforce that can be apprehensive or resistant towards the latest advances of today, and how to forecast innovation projects.
Many organizations are focused on being ‘Data Centric’, ‘Data Driven’, and monetizing on data because it’s the new enterprise oil. However, most organizations fail to make the pivot, with nearly 73% of organizations fall short of what they set out to accomplish with their data strategy. This discussion will go into all the reasons ‘Why’, and what we can do to course correct, evangelize, and create a movement that will build a lasting legacy with data. Everyone can be data-centric without removing the creativity, critical thinking, and experience we bring to the table.
Change is hard. Disruption is hard. With the pace of change being the fastest it’s ever been, leaders have an unfair advantage in today’s world. Constantly distracted by messages and emails, combined with the pressures of motivating teams, aligning strategic priorities, balancing workloads, and all while innovating, leaders are not set up to succeed, UNLESS THEY GO ROGUE. This discussion is all about finding the rogue in us. The leader who focuses on not being busy but being productive. The leader who let’s go of the need to respond in exchange for the need to reflect. Leaders who, in spite of resistance, can see beyond the trees and around the corner and put forth passion and relentless pursuit to achieve what needs to be accomplished, and all while staying sane. This discussion is about managing our energy so we can show up in the right way, at the right time, and for the right people to drive change and create outcomes.
The goal of AI is to amplify and accelerate what we do best in order to do MORE with the SAME (not less). So, how do you prepare your organization model post-launch? What is the new Operating Model after deployment? What considerations and assumptions do you need to know NOW to achieve your ROI, establish a regenerative growth model, and drive “Catalytic commerce” – where AI is an enabler that creates compounding value generation vs. taking a one-time slingshot approach with barely any returns.
As some employees adopt AI, while others resist it, AI will undoubtedly be a part of a company fabric, no matter what scale of AI you’re deploying, and it will come in various forms, the adoption of AI Agents, AI Models, and/or embedded AI systems (like Microsoft’s co-pilot, Salesforce, Snowflake, etc). What should you do to prepare for this human + AI workforce integration? What should you look out for? What assumptions won’t hold true? How should your HR, Leadership, and Middle-Management teams proactively plan for what’s to come in the next 1-3 years?
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