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Episode 1: Unleash Your Inner AI Hero

An Unscripted Companion Guide

Welcome to the next step in your AI journey! For those seeking real experiences and tangible lessons on innovating through data, you’ve come to the right place. Read our Guide for insights from our Visionary Voices – respected practitioners across data and analytics. Introduced by Deepa Tambe, Head of Reporting Technology at Barts Health NHS Trust, the Guide is designed to help data professionals maximize the potential of AI.

Meet the Cast

Brendan Grady

Brendan Grady
EVP and GM, AI and Analytics BU Qlik
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Speaks About
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Rachel Terry

Rachel Terry
Head of Sustainability, Van Oord
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Speaks About
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Brian Torio

Brian Torio
Managing Director, AI and Data, Deloitte Consulting
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Speaks About
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Julie Kae

Qlik
Julie Kae
VP Sustainability and DE&I, Qlik & Executive Director, Qlik.org
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Qlik
Speaks About
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Tim Zhou

Accenture
Tim Zhou
Managing Director of Data & AI,
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Accenture
Speaks About
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Henri Rufin

Radiall
Henri Rufin
Head of Data & Analytics
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Radiall
“At Radiall, we learn by doing and we believe in proof of concept. AI is definitely something we want to investigate. While we must deal with extra care with generative AI, we can not stay idle and be scared by the danger these technologies hold. We have started an AI initiative which, I hope, will lead us someday to deliver new services to support data literacy and data governance across the company. We work closely with IT and security departments to minimize risk, but also by establishing a trusted group of people to experiment alongside you, before rolling something out to the public.”
Speaks About
Public vs Private Models
Experimentation
Lessons Learned

Rahul Gupta

HCL Technologies
Rahul Gupta
Associate General Manager
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HCL Technologies
“We have a data scientist team which works in Python and has created many ML models for business uses. One example is the Attrition Prediction Analysis – which helps us predict which employees are at risk of leaving the organization and allows us to support them accordingly.”
Speaks About
Defining Needs
Public vs Private Models

Michal Lecian

Dolphin Consulting
Michal Lecian
Business Intelligence Analyst
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Dolphin Consulting
“AI enables me to better understand the relationship and context of data that I might not have noticed at first. It has also led me to question certain things that I wouldn’t have questioned before when analysing manually”
Speaks About
Lessons Learned

Martin Sahlin

Stretch Qonnect
Martin Sahlin
Founder & CEO
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Stretch Qonnect
“Everyone is talking about AI, but many don’t know why or what to do with it. In order to get the right outcome and not to go down the wrong path and believe in something wrong, initiatives and investments in AI need to have a very clear and particular challenge in mind. What’s more, there needs to be a tangible measuring of the outcome.”
Speaks About
Defining Needs
AI Job Roles

Filippo Orlando

Unieuro S.p.A.
Filippo Orlando
Head of Advanced Analytics
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Unieuro S.p.A.
‘’AI enhances our team's capabilities by automating tasks, providing insights and improving efficiency. It's reshaping roles to focus on higher-level strategic tasks. In some cases, new AI-focused roles have emerged to manage and optimize AI systems.’’
Speaks About
AI Job Roles
Reducing Risk
Governance and Security

John Delligatti

SDI
John Delligatti
Director of Digital Supply Chain Transformation
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SDI
“It's one thing if AI saves me, personally, a bunch of time, but if I can save 10 or a hundred people time – it's got tremendous value. So, I would say begin investigating these tools right away. Encourage your team members to use them.”
Speaks About
Speed
Public vs Private Models
Lessons Learned

Priscila Papazissis

Localiza&Co
Priscila Papazissis
Data Product Manager
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Localiza&Co
“AI is transforming access to data and analytics and promoting data driven decision-making in my organization. It brings about the opportunity to capture, treat and show huge amounts of data in faster ways than ever before thanks to machine learning algorithms. Now the time between the business event and collecting the results has reduced so we are informed faster and can make decisions that make a difference.”
Speaks About
Speed
Uncertainty
Innovation

Mario De Felipe Pérez

Grupo ASV
Mario De Felipe Pérez
Chief Data Officer
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Grupo ASV
“We are relying on specialized partners to deploy the technology. If it reaches sufficient maturity and relevance within the company, we will consider incorporating specialized personnel. What we are doing is training many people within the company in Artificial Intelligence. Mainly, we are working on how to use Generative AI to increase productivity in our call centres and in departments such as legal, financial or marketing.”
Speaks About
AI Job Roles
Governance and Security
Lessons Learned

Deepa Tambe

Barts Health NHS Trust
Deepa Tambe
Head Of Reporting Technology
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Barts Health NHS Trust
“In healthcare we collect tons of data from every interaction with patients and machines. What we need is the use of data for building insights. Predicting the pressure points, predicting the flow of patients in the emergency department and the resources needed to cater to the high demand of the hospitals are areas I believe it could really help. We are already using predictive analytics and alerting mechanism to notify operational teams for the correct bed type requirements. This was developed during the peak of the pandemic which hospitals found very useful.”
Speaks About
Information to Insights
Uncertainty
Public vs Private Models
Lessons Learned

Mark Little

Mayborn Group Limited
Mark Little
Principle Business Intelligence Specialist
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Mayborn Group Limited
“We’ve used AI for a number of things. The one we have seen the biggest return from is sentiment analysis. Using the technology, we can look at all our reviews from across a number of platforms and get a general idea of how we are performing. Without it we’d have to spend hours collating and reading all the text.”
Speaks About
Information to Insights
Defining Needs

Calum MacIver

The Health Information Service
Calum MacIver
Corporate Information Manager
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The Health Information Service
“Within the NHS, AI is becoming more and more visible in its use, from assisting diagnostics to predicting admission and attendances. The analysis we are seeing from the technology is opening up new avenues for research from all areas of the health service.”
Speaks About
Information to Insights
Uncertainty

Dave Elliot

Mayborn Group Limited
Dave Elliot
Solutions and Data Innovation Manager
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Mayborn Group Limited
“AI provides a vast array of opportunities… be that improving and optimizing the supply chain, enhancing the consumer experience through natural language processing or generative AI, or through core AI functions such as sales or demand forecasting.”
Speaks About
Information to Insights
Public vs Private Models
Reducing Risk
Lessons Learned

Mitul Vadgama

Lloyds Banking Group
Mitul Vadgama
Senior Data and Analytics Strategy Manager
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Lloyds Banking Group
“AI has the potential to transform financial services, such as banks, by providing personalized services, enhancing security, optimizing operations and enabling data-driven decisions. Adopting AI technologies can help banks stay competitive in a rapidly evolving industry, while delivering better services to their customers.”
Speaks About
Information to Insights
Innovation
Lessons Learned
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Foreword

Written by Ronald van Loon

CEO & Principal, Intelligent World

The GenAI Effect: Disruption, Opportunity and the Future of Business

We are witnessing a transformative era of advances in AI. This has been most notably marked by its mass consumer adoption enabled by the rise of accessible innovations in General Artificial Intelligence (GenAI). 

In its relatively short time in the spotlight, the GenAI landscape has evolved rapidly. Now, the focus has turned to how businesses can take advantage of its seemingly infinite potential.  

While current sentiment towards GenAI feels like cautious optimism, strategic adaptation and a collective effort towards responsible stewardship, the path to creating commercial value from this powerful technology is still being trodden. Despite this, adoption rates are nothing short of remarkable. According to Qlik’s Generative AI Benchmark Report, 79% of business leaders have already invested in a GenAI tool or project.

However, with great power comes great responsibility. The level of disruption caused by AI and GenAI will be significant across many industries, requiring an urgent and proactive approach to governance and risk management. At this point, most organizations don’t have robust policies in place on how they, and employees who may already be using it in their personal lives, interact with the technology.

The ethical and security concerns associated with AI and GenAI are abundant, demonstrated by the focus of President Biden’s AI Executive Order establishing new standards for AI safety, and the recent AI Global Safety Summit in London, which culminated in the Bletchley Declaration on AI Safety.

These developments underscore a global commitment to ensuring the safe and responsible development of AI. The emphasis on international collaboration, consumer protection and promotion of innovation reflects a balanced approach, aiming to harness the benefits of GenAI while mitigating its risks.

But even as governments consolidate their responses to innovation, GenAI is already having a tangible impact on how businesses operate. It's re-shaping how they view hiring and workforce skills, given its increasing use in functions like marketing, sales and customer care. At the same time, demand for data engineers, machine learning engineers and AI data scientists is rocketing, with emerging roles like prompt engineer also gaining prominence. It’s these workers who will shape the commercial response to AI innovation.

These changes appear to have been met with optimism and a strategic approach to investment, rather than inertia – 45% of executives indicate that recent advances in AI are driving an increase in AI investment, while 36% are investing in a formalized AI strategy.

That’s a good start, but action does not always deliver positive impact. This guide features perspectives from data and analytics leaders across multiple industries who are on their own AI journeys, providing tangible tips from those responsible for optimizing data processes with AI.

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