Paul Zikopoulos

Future Trends Expert, and VP of Technology Group Skills Vitality & Enablement at IBM
  • Offers a technology framework to help clients “create spend money to save money/make money” strategies to excel in a time of rapid change
  • Explains why AI and big data aren’t just competitive edge tools — they’ve become survival tools
  • Gets to the heart of evolving technology issues, including the implications of Generative AI (like ChatGPT) as it relates to ethics, bias, and transparency so you can use AI responsibly
  • Leads a presentation full of energy, humor, incredible visuals, and live demos so you can see it for real in action

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In a rapidly transforming world, data has become the new competitive advantage. And according to future trends expert Paul Zikopoulos, “Every day we walk by solvable problems, leaving opportunities untapped.” The VP of Technology Unit Skills & Enablement at IBM, Zikopoulos discusses how working these “solvable problems” creates disruption in the marketplace and how golden signals of opportunity can be found within mountains of noise. At IBM, Paul leads from the front, owning accountability and strategic direction in a “tech years are like dog years” world for the entire IBM Technology Unit’s (all IBM software and hardware) sales, tech sales, and partner ecosystem learning journeys, and upskilling programs.

Exclusively represented by Leading Authorities speakers bureau for lectures, Paul is changing the way audiences are looking at their businesses in terms of potential sales, obstacles, potential for growth, and how they utilize technology, such as generative AI and cloud applications, to support their organizations. Paul shares future trends that are starting to happen in real-time and have multiple applications: from garbage cans that alert sanitation departments when they need collection – saving cities millions – to shampoo brands that are connecting weather forecasts with personal consumer profiles to suggest the right mix of hair products for the day. He easily discusses the next generation of technological change from the power of machine learning and voice-to-text, to the opportunities in reading digital body language and joining the Internet of Things trillion sensor economy, and more.

Incredibly energetic and easy to follow, Paul is the antithesis of what many people think of when they consider a big data expert. Using incredible visuals, including a hashtag aggregator that instantly creates examples of perfectly segmented consumers live on stage, Paul amazes audiences with the amount of information available to change the conversation about your industry. By sharing his insights on where big data comes from and the idea that “If you aren’t paying for it, you are being sold,” Paul breaks apart the roles of data collection and decision making for executives seeking the opportunities for disrupting their industry and leap-frogging the competition.

Paul is an award-winning tech thought leader and writer who has shared his expertise on AI and big data on the popular TV show, 60 Minutes, as well as in publications such as Technopedia and Analytics Week. He has published 21 books, including Cloud Without Compromise, The AI Ladder, and three ‘For Dummies’ titles, and more than 360 articles during his, as he calls it, accidental 28-year career as a data nerd — which he began with no prior coding experience. Among the leading voices in tech and big data, Paul has been named in dozens of global “Experts to Follow” & “Influencers” lists, including Analytics Insight’s “Top 100 Global AI & Big Data Influencers” and SAP’s “50 Big Data Twitter Influencers.” Currently, he is writing an O’Reilly book on Hybrid Cloud. An expert in harnessing the power of big data, Paul brings real world experience from his at time managing more than 1,400 professionals to help groups build influence and affect change in their organization. 

Paul has taken an active role in bolstering Women in Technology, LGBT and general workplace inclusivity (completing an intensive D&I certificate at Cornell University), and Coding for Veterans. In addition to being the first and only male ever to be recognized as an IBM Canada “Women in Technology Ally of the Year” award winner, he is a seated board member for Switch (formerly known as Women 2.0), a global network and social platform for aspiring and current female founders of technology ventures who he became involved with after one of his tweets was mentioned on the TV show “The View.” He is also on the world-recognized Masters of Management Analytics and AI program boards at Canada’s prestigious Queen’s University.

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Insights 2015 Keynote Highlights

Leading Authorities Speakers Bureau's Future Trends Speakers

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The Big Deal About Big Data. Is there a more frequently used term than Big Data these days? It’s changing the world, but we don’t yet know how it will sell, operate, learn, heal, and determine big decisions. In this session audiences get a quick framework by which to identify and understand Big Data (hint: it’s more than Tweets and Facebook “likes”), and how it’s being used across industries to transform the norm. In addition, get insight into what modern analytic architectures look like—you’ll hear about governance, data lakes, snow flakes, and more. Zikopoulos will leave you with not only a great understanding of Big Data, but also how you are going to change the world with it.

Diversity-Centered Team Transformation and Leadership. Paul is a leading voice when it comes to shining the light on the importance of diversity in tech. A board member of Switch (formerly known as Women 2.0) and the only male recipient of the IBM Canada “Women in Technology Advocate of the Year” award, he has long advocated for the viewpoints and contributions of people of different races, genders, and backgrounds, and has built innovative, industry-defining teams with diversity at the core. In this talk, Paul shares his proven strategies for developing diverse, high-performing teams meant to disrupt the status quo, rather than fill a quota.

Generative AI: The Good, The Bad, and the ChatGPT. While AI has gone through many hype cycles, seemingly overnight, it went from a "need to eventually have…" type of conversation to one that is "needed to be had last month." Even to skeptics, the release of ChatGPT seems to have marked a turning point with AI able to tell jokes, churn out essays that look human-written, and oh so much more. And while ChatGPT has captured the world's imagination, the real question is if AI is actually ready to deliver a transformative change for companies. The answer, unequivocally, is "Yes." Of course, the use cases for Generative AI seem to grow by the week as it becomes obvious this type of AI presents unparalleled opportunities for business to enhance productivity, streamline processes, and improve decision-making. 

In this high-octane demo-rich keynote, Paul Zikopoulos (an award-winning author and speaker who's been named to numerous "Thought Leader" and "People to Follow" lists on the topic of data and AI, including CIO Look's "Top 10 Most Intelligent Leaders in Data Science & Analytics") delves into the topic of Generative AI in a language everyone can easily understand: Just what is it? How does it work? What are the opportunities across all industries. Despite the possibilities generative AI presents, it’s not all a fairy tale. There are data and security concerns to consider, and what’s the extent to which we can trust all of this technology that’s coming at us hard and fast? There's no question that generative AI will usher in a new democratized relationship with AI, but there's a lot to understand on how this type of AI is made, its pitfalls, the opportunity for fine-tuning, safety, responsible use, and more. This keynote will not just help attendees demystify the new world of Generative AI, but help them prepare a strategy to execute and take the next steps in this pivotal moment for business. 

Future Tech Trends. Today’s competitive advantage lies in data. Everyday we walk by solvable problems, leaving opportunities on the table. According to big data expert Paul Zikopoulos, it is exactly these kinds of solvable problems that disrupt industries and create new businesses. In his presentation, Paul outlines the forces driving innovation and discusses how technologies from machine learning to cloud computing will shape the future and how social, mobile, and the internet of things will change how we interact with businesses and each other.

Women in Technology. Spoiler Alert: Paul is male. But the advancement of Women in Technology is one where men must be allies. After managing and growing hundreds of careers first hand, Paul brings an entertaining and insightful point of view into women in technology with sound advice on how to build confidence, grow personal careers, and pay it forward.

Internet of Things. From milk cartons with temperature controlling tags to tee-shirts that monitor the vitals of post-operation patients after they leave the hospital, the merging of technology and data is taking consumers into the future of tech. Paul discusses the profound effects of this new technological frontier and teaches audiences where their business model can benefit from new applications of data.

Disruption. In a world where Facebook is the biggest media company but creates no content, Uber is the largest taxi service but owns no cars, and AirBnB is one of the most popular places to book a place to stay but owns no buildings, data is the new competitive advantage. Paul breaks down the main business factors disrupting the marketplace and what you can do as a business to succeed in such a time of change. Paul then goes one step further to predict the industries ripe for disruption and identify potential new products that will change the way we work and live.

Monetization of Data: Data Collection is 24/7 but Decision Making is Not. Most consumers and businesses may not realize that if you are not paying for it, you are probably being sold. Paul uses live examples from twitter to show how much data is readily available and how quickly statistics from one hashtag can be used to segment a market and create a potential consumer profile. Paul pulls from current case studies to explain how unlikely business partnerships can be the most profitable and strategic when capitalizing on data.

Leadership and Career Building From Mentor to Mentee. As a recognized top mentor at IBM, and a leader of organizations from 10 to well over 1,000, Paul brings over 21 years of experience, stories, and frank observations into building teams, careers, how to mentor, what makes for great leadership, and the kinds of people to never be (or work for). This energetic talk is all about transferring energy from stage and into your teams.

The Power of STEM. Science, Technology, Engineering, and Math (STEM) skills are the currency of the future. Sadly, our continental market place isn’t equipping itself at the rate of innovation needed. STEM paths start much earlier than anyone think: Indeed, youth are making pivotal decisions in Grade 4 that place them on a path. In high school there are more key decision points around STEM skills. Paul uses his unique ability to ‘connect’ with youth with an invigorating talk that can be tailored from Grade 4 to high school students and the power of STEM.

Unstuck: How to Foster Personal Career Growth. Ever feel stuck, and can’t figure out how to turn around? The definition of stuck will vary, some of you will be stuck in a “3rd World” way and that’s serious; some of you will be stuck in a “Champagne” way, and guess what, that’s serious too. It’s all relative. And while you can’t have “Champagne” stuck if you have “3rd World” stuck (consider yourself lucky to be “Champagne” stuck!), stuck is still, well, stuck.

I’ve been stuck my whole life. You know why? Spoiler alert: I’m human. The death of my first child, Grace, still leaves me stuck. I’ve been work stuck more times than I can remember. Over the course of your career, you should expect to feel stuck. Those gears are going to stop spinning fast and you’re going to have to replace some parts. If you’re not actively maintaining that engine, it’s no wonder why it’s stuck. It’s a fact: people and things get stuck – in relationships (friends and significant others), work, life and so on.

The position of stuck, as external of a force as it seems, ironically starts from within. And I can tell you that almost every single major professional accomplishment I’ve achieved was from the position of stuck. The stories behind finishing my MBA, becoming an award-winning and professional writer/speaker, getting approached by the TV show 60 Minutes or called out on The View, getting involved with Women in Technology, any highlight I could share in my 23 years came from the position of stuck.

It’s the “how I deal with stuck” that created an avalanche of professional accomplishment, at least for me. This talk is about career stuck. I’m going to share with you strategies to get un-stuck, and the things that, every single time, over any accomplishment I’ve had, were present.

Remember this: you’re not a tree. If you don’t like where you are, you can move. Ready to get things moving? Let’s get unstuck!

Live, Buy, Try, or Die — What's in Your AI? Trust is a foundational building block of society. When you board a transportation medium on autopilot (trains, planes, and soon to be automobiles) we are intrinsically expressing trust on the people that created these technologies and the service (and answers) it provides. But what about AI. AI knowledge and behavior is one that evolves over time … it’s not a point in time thing.

If we accept that AI is going to be a relevant part of our future, it is important to establish the foundations of trust in AI systems and foundation models — this includes tools such as ChatGPT, Midjourney, DALL-E, Lensa, Jasper, and all of the other emerging AI tech we’ve been hearing about in the news. Today, we regularly rely on AI models without having a clear understanding of their capabilities, knowledge or training processes. Not only can this present danger, but it can create challenges in governance adherence (GDPR), earning business, protecting consumers, reputations, and more. 

There is an old Canadian hockey saying, “Don’t go to where the puck is, go where it’s going to be”. Trust, ethics, and bias isn’t getting as much attention (outside of research) as it should … but with regulations such as GDPR and the ubiquitous headlines of data lost or mis-used … this is the big discussion you have be having (or will soon be forced to have) in the board room as you plan out your AI strategy or evolve it. (Spoiler alert: conversations had before you are forced to have them always put you on a faster path to success, mitigate costs, and separate you from your peer groups.)

In this session you’ll learn about a framework for build trust into AI. You’ll understand bias and how it can influence models, and how to spot bad bias and acceptable bias as well. You’ll learn about explainability, its effect on society, and more so how it can help infuse AI "take rates" across the business. You’ll also learn about ‘safe’ AI … from hacker, crackers, and spies (oh my!) but also societally safe AI as well. In short, you’ll be where the AI puck is going to be. 

Bottom line: You need AI that is transparent so we can inspect the algorithms to make sure they’re doing the right things and just like how early automobiles didn’t always drive straight, have seat belts, or window wipers (all safety mechanism), our early AI algorithms are going to need bumpers for safety.

(Note: this is a great follow up session to my keynote “The Mysterious World of a Thinking Business” where you hear about these concepts, see them in action, and their use cases … or the this is the “How It Works & Your Rightful Seat at AI Table”).

How It Works & and Your Rightful Seat at AI Table. How does Alexa know most of the time what you are saying? How does a computer find a face in a picture and then magically tells you who it is? (It starts the same way your camera puts that yellow box around a face when it's ready to take a picture.) How can a computer convert English into Spanish (or almost any language for that matter) with accuracy that puts to shame 20 year old expert made translation systems? How can a computer read an online review and come up with a rating? Or how does it seemingly understand a passage of text with respect to who, where, what, when, and more?

I’m not a data scientist (presumably neither are you). I have no plans to be a data scientist. I think data science is interesting and I want to learn more about it. MOST OF ALL I wanted to know when data scientists (or anyone for that matter) are talking around me so they could go off and do their next project. After all, I owned the business, I needed to have an understanding … I needed to keep my seat at the "AI Game of Thrones Table" and thus I set out to learn how this stuff works.

In this interactive presentation, the audience votes in real-time what they want to hear about and how it works. Not a techy? Even better, words such as ‘back propagation’ and ‘morphological operations’ have been banished from this talk so the every day person can see how stuff is done behind the scenes.

Packed with lives demos and some fun, you’ll leave this session with a sound understanding of the “How of AI” and up your game in strategic conversations around the AI strategy for your enterprise.

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