Four panelists who spoke about AI and skills

Responding to the impact of the pandemic, we will need to get our economies back on track – which means businesses need to navigate the now, plan for re-booting and re-invent to shape the ‘next normal.’

According to Ralph Haupter, President, Microsoft EMEA, it will require “three critical areas of focus: human ingenuity, adaptability, and innovation.” He sees that digital transformation has accelerated as firms look to stabilize and get back to growth, with projects that may normally take years being delivered in months, and that “most innovation right now has, at its heart, an AI component.”

This set the scene for a lively expert panel debate which explored key questions around the role of artificial intelligence, employee skills and augmenting human ingenuity in helping firms be adaptive and resilient.

The discussion was chaired by Azeem Azhar, founder of the Exponential View, with executives from global engineering, management and development consultancy Mott MacDonald, AI start-up Robovision and technology advisory firm Fourkind, joined by Ralph Haupter.

Jonathan Berte, Founder & CEO of Robovision, echoed Ralph’s observation around accelerated digital transformation and noted that “it’s all part of this bigger journey to making digital twins of companies and societies. And what we see is that companies embracing AI, they just have more knowledge. They have more digitalization in their process and this brings a lot of advantages.”

Mott MacDonald is one of the organizations seeing significant positive business impact, according to Simon Denton, Business Architect, who gave a number of compelling examples: “We’re taking advantage of AI through services like Project Cortex, which is really enhancing our knowledge management within the organization, with its reducing the dangers of knowledge being trapped. Again, this is one of those sort of silent AI partners that’s really helping to connect the organization and bring it together to help us achieve our mission.”

Jarno Kartela, Machine Learning Partner at Fourkind, sees huge potential in AI increasingly augmenting workers. That means skills like creativity and problem-solving become more important than ever before. “Technology like machine learning lets you simulate business environments, different outcomes and predict possible end results. I think that creates a lot of resilience for the companies adopting this type of technology. But, at the same time, I think creative problem solving and strategic design skills will become even more important because machine learning will move from automating things to helping augment people to solve problems. This will become even more important in times like these.”

Simon offered some practical advice for businesses at the early stages of AI implementation: “It’s about building confidence and trust in AI. I think if people are starting [their AI] journey, it’s about getting your data in order.” The sentiment of moving forward with confidence was shared by Jarno, “We shouldn’t be afraid of using emerging technology and augmenting human skills because it’s not really about losing control, but improving our own decision-making.” And Jonathan encouraged business leaders not to wait and risk ceding market share: “Don’t fall into the trap of analysis paralysis and over analyze your road to AI. Just jump into it.”

You can dive into the full debate here, and a full transcript is below:

Part 1: The panel discusses digital transformation and AI, the role of skills and augmenting employees, what it means for business adaptability and resiliency, and managing uncertainty in the ‘new normal.’

 

Part 2: The conversation picks up on curating AI models, and moves onto why some business functions lead with AI while others lag, advice for organizations less far along their AI journey, and the role of culture and leadership.

 


 

Full transcript

PART 1

AZEEM:

IT IS VERY EXCITING TO BE HERE. AND TO BE ABLE TO HEAR FROM A NUMBER OF EXPERTS WHO ARE THEMSELVES, ACROSS MANY DIFFERENT TIME ZONES, ON KEY QUESTIONS RELATING TO HOW THE INVESTMENT IN ARTIFICIAL INTELLIGENCE AND IN PARTICULAR THE INVESTMENT INTO THE SKILLS OF YOUR WORKERS HAS MADE FIRMS MORE CAPABLE OF ADAPTING TO THE NEW NORMAL THAT THIS CRAZY YEAR OF 2020 KEEPS THROWING AT US.

SO OUR PANEL OF EXPERTS SHARED THEIR EXPERIENCES WITH US, AND WE WILL ALSO HEAR FROM MICROSOFT EMEA PRESIDENT RALPH HAUPTER ON AI, AND THE MANY CUSTOMERS THEIR FIRM HAS HELPED.

AS WE STEP INTO OUR DISCUSSION, MAYBE IT IS WORTH SPENDING A FEW SECONDS TALKING ABOUT WHAT WE MEAN BY AI IN THE CONTEXT OF OUR DISCUSSION TODAY. IT IS SUCH A TERM THAT HAS CAPTURED THE IMAGINATION IN MANY DIFFERENT WAYS, BUT FOR BUSINESSES, I SEE IT AS A VERY PRACTICAL SET OF TOOLS THAT ARE AVAILABLE TODAY FOR COMPANIES TO MAKE USE OF FOR THE BENEFITS OF THEIR CUSTOMERS, THEIR INTERNAL OPERATIONS, PRODUCT DEVELOPMENT. IT IS A SET OF TECHNOLOGIES AND PRODUCTS THAT AT THEIR HEART HAVE THE NOTION OF COMPUTER SYSTEMS THAT ARE PERFORMING THEIR ACTIONS ON THE BASIS NOT PURELY BY WHAT THEIR PROGRAMMERS HAVE TOLD THEM TO DO, BUT FROM LEARNING FROM THE DATA AND THE ENVIRONMENTAL EXPERIENCES THAT THESE SYSTEMS EXPERIENCE. NOW, THESE TASKS COULD BE SIMPLE THINGS LIKE RECOGNIZING OBJECTS, FOR EXAMPLE HANDWRITING AND IMAGES, OR THINGS I’M SURE MANY OF US HAVE EXPERIENCED, TO OUR DELIGHT, ENGAGING IN LIFELIKE CONVERSATIONS WITH CHATBOTS OR THINGS THAT HAPPEN UNDERNEATH THE SURFACE OF OUR INTERACTIONS WITH COMPANIES, BY OPTIMIZING THE ALLOCATION RESOURCES ACROSS A NETWORK OR SUPPLY CHAIN. AT THE HEART IS DATA PREDICTION, OPTIMIZATION LEARNING, VERY PRACTICAL CORE TECHNOLOGIES THAT CAN HELP ANY BUSINESS. BUT LIKE SO MANY OF THE TECHNOLOGY TRANSFORMATIONS WE HAVE SEEN BEFORE, WHETHER IT WAS THE MOVE TO CLOUD OR CRM OR EVEN RELATIONAL DATABASES EARLIER IN OUR HISTORY, THIS IS A TECHNOLOGY THAT IMPACTS HOW EMPLOYEES ACT AND HOW THEY ARE ORGANIZED AS MUCH AS IT AFFECTS AN I.T. DEPARTMENT AND AS MUCH AS IT AFFECTS THE STRATEGIES IN A BUSINESS. AS A TECHNOLOGY, IT IS ONE OF THOSE THINGS THAT DEMAND A LOT FROM THE EMPLOYEE AND THE WAY IN WHICH COMPANIES SCALE UP THEIR WORKERS.

TO HAVE THIS DISCUSSION, WE HAVE BEEN VERY LUCKY TO HAVE SOME EXPERTS WHO HAVE SOME HANDS-ON EXPERIENCE WITH THIS. WE WILL ASK EACH OF THEM TO GIVE A LITTLE ONE MINUTE INTRO INTO THEIR COMPANY’S BUSINESS AND MISSION ON THEIR OWN ROLE. WE HAVE SIMON, JONATHAN, JARNO FROM FOURKIND, AND I WILL ASK RALPH FROM MICROSOFT TO SAY  A FEW WORDS. PERHAPS WE COULD START WITH YOU, SIMON.

SIMON: HI, I AM SIMON DENTON. WE ARE A GLOBAL MANAGEMENT AND DEVELOPMENT CONSULTANCY, SO AROUND THE WORLD WE HELP CLIENTS WITH INFRASTRUCTURE NEEDS FOR TRANSPORT, ENERGY, WATER, AND THE ENVIRONMENT. YOU MAY NOT HAVE HEARD OF US MUCH, BUT WE ARE ON SOME EPIC PROJECTS WITH TRANSFORMING RAIL NETWORKS IN LOS ANGELES AND SYDNEY, TO SHAPING THE BIGGEST ENERGY FARMS. WE SECURE WATER SUPPLIES TO CITIES LIKE NEW YORK AND LONDON. WE ARE UNIQUELY POSITIONED TO BRIDGE THE PHYSICAL AND THE VIRTUAL DIVIDE. MY ROLE IS TO FACILITATE CONNECTIONS WITHIN THE ORGANIZATION AND EMPOWER OUR STAFF TO DO WHAT THEY DO BEST AND TO SERVE THEIR CLIENTS WELL.

AZEEM: THANK YOU VERY MUCH, SIMON. JONATHAN, COULD WE TURN TO YOU FOR A BRIEF INTRODUCTION.

JONATHAN: YES, I AM THE FOUNDER OF ROBOVISION. IT IS ALL ABOUT DEMOCRATIZING AI. YOU WANT TO GET AI FROM THE DATA SCIENTIST DEPARTMENT TO SPECIALISTS AND NORMAL PEOPLE EVERYWHERE SO THEY CAN BUILD THEIR OWN DEEP LEARNING MODELS, CREATE THE DATA, ANNOTATE IT WITH THE HELP OF THE CLOUD, AND IN THIS WAY WE ARE DEVELOPING EASY TOOLS WITH MANUFACTURING, AGRICULTURE, SMART NATIONS, AND THE LIFE SCIENCES. WE ARE ALSO HELPING THE COVID-19 CRISIS BY ENABLING RADIOLOGISTS TO CREATE DEEP LEARNING MODELS THEMSELVES AND TO MORE QUICKLY ANALYZE CT SCANS WITH COVID RELATED DAMAGES.

AZEEM: THANK YOU VERY MUCH. JARNO FROM FOURKIND.

JARNO: HELLO. WE AT FOURKIND ARE A BUSINESS FOCUSED ADVISORY COMPANY WITH DEEP KNOWLEDE IN MACHINE LEARNING, AND WOULD LIKE TO SOLVE PROBLEMS THAT OTHERS CLAIM UNSOLVABLE, RANGING FROM MAKING WHISKY WITH COMPUTERS TO UTILIZING AIRPORTS. WE HAVE 12 YEARS OF EXPERIENCE FROM STRATEGY TO DEVELOPMENT, AND I AM SUPER EXCITED TO WHAT WE WILL DO NEXT BECAUSE I THINK WE HAVE ONLY JUST TOUCHED WHAT IS POSSIBLE. THANKS.

AZEEM: THANK YOU, JARNO. NOW YOU’RE MAKING ME THIRSTY, GIVEN SOME OF YOUR WONDERFUL INNOVATIONS. RALPH, THANK YOU FOR JOINING US. I THINK YOU ARE STILL IN ASIA AT THE MOMENT, BUT IT WOULD BE WONDERFUL TO HEAR YOUR PERSPECTIVE ON AI SKILLS COMPONENT, WHAT YOU’RE SEEING FROM THE RESEARCH AND WHAT THAT MEANS FOR LEADERSHIP.

RALPH: THANK YOU FOR GIVING ME THE OPPORTUNITY HERE. I WOULD BE READY FOR WHISKY, TO BE HONEST, FROM A TIMING PERSPECTIVE. WE SEE IN THESE TIMES WHERE WE HAVE DISRUPTION, A LOT OF FOCUS RIGHT NOW IS ON HOW TO STABILIZE AND GO BACK TO GROWTH. THE EXPERIENCE WE HAVE RIGHT NOW IS THAT THERE ARE THREE CRITICAL AREAS TO FOCUS ON. ONE IS HUMAN INGENUITY, THE OTHER IS ADAPTABILITY. FINALLY THE FOCUS ON INNOVATION. INNOVATION IS RIGHT NOW HAPPENING, TECHNICAL INNOVATION IS HAPPENING AS WE SEE AND SPEAK, AND AS WAS MENTIONED, WE LITERALLY SEE PROJECTS WHICH NORMALLY TAKE TWO YEARS HAPPENING IN TWO MONTHS BY JUST PUTTING UP INNOVATION BACK TO BEING A DRIVER FOR GROWTH.

MOST OF THESE INNOVATIONS RIGHT NOW, ARE HAVING IN THEIR HEART, AN AI COMPONENT. AS AN EXAMPLE, WE SAW IN DENMARK DURING THE CRISIS IN COPENHAGEN, THE EMERGENCY MEDICAL SERVICE THERE, BUILDING A CHATBOT. AND WITHIN A DAY THEY COULD HAVE 30,000 CALLS FOR CLARIFICATION IF PEOPLE HAD INDICATIONS OF INFECTION. THAT WAS DONE WITH AI IN A COUPLE OF DAYS, AND IT SHOWS THE POWER OF INNOVATION AND HOW IT COMES TOGETHERWE THINK THAT TECHNOLOGY IS HERE TO NAVIAGTE THE NOW,IT’S HERE FOR  PLANNING TO REBOOT, AND NOW WE’RE AT THE PHASE OF RESHAPING THE NEXT NORMAL. EVERY ORGANIZATION IS GOING THROUGH THAT, WONDERING WHAT TO DO. DISCOVERING HOW AI CAN HELP AND FIGURE OUT WHAT IT MEANS FOR THE CULTURE OF THE ORGANIZATION.

SO WE WENT ON THAT AND TRIED TO UNDERSTAND WHAT IS THE EMPLOYEES’ IMPACT AND WHAT IS THE ROLE OF THE EMPLOYEE IN THIS GROWTH OF AI? WE FOCUSED ON THE SKILLS COMPONENT OF THE EMPLOYEES IN THAT CONTEXT. WE DID RESEARCH WHERE WE WERE IN MARCH AT THE TIME OF THE CORONAVIRUS PEAK. WE WENT IN MORE THAN 20 COUNTRIES TO MORE THAN 12,000 EXECUTIVES AND ASKED THEM AND THEIR EMPLOYEES ABOUT TECHNOLOGY USAGE, THE IMPACT ON AI AND THEIR SKILLING. WE FOUND A COUPLE OF INTERESTING DATA POINTS.  93% OF THE FIRMS ARE SAYING THEY HAVE ACTIVELY BUILT SKILLS FOR THE WORKERS TO WORK WITH AI. 70% OF THEM SAY EMPLOYEES ARE PREPARING THEM FOR AI, WHICH I THINK IS GOOD NEWS, A STRONG CORRELATION BETWEEN A COMPANY’S IMPACT AND THE EMPLOYEES’ TRAINING. SO TWO THIRDS OF TODAY’S WORKERS ARE MENTORED BY AI.

WHAT IS THE OUTCOME? IT IS BUSINESS EFFICIENCY, BUT IT IS ALSO SPEED AND CHANGE OF PRODUCT DEVELOPMENT AND SERVICE AND EXPERIENCE ON AN AI BASIS, AND EVEN MORE IT IS A CHANGE ON THE CULTURE OF INNOVATION CULTURE. SO I PERSONALLY WOULD SAY I HAVE SEEN THROUGH AI CHANGES IN CULTURES OF THE COMPANY HAPPENING. LEADERS EMBRACING DATA , WHICH IN MANY WAYS IS THE FOUNDATION FOR AN AI EXPERIENCE, LEVERAGING THAT ONTO RESHAPING COMPANIES. NINE OUT OF 10 EXECUTIVES SAY THEY BENEFIT FROM AI, THE SUPPORT WHERE THEY HAVE EXPERIENCED IT ONCE. THIS ALL IS ABOUT IMPROVEMENT. YOU SKILLE PEOPLE, YOU HAVE BETTER OUTCOME. IT IS A COMBINATION OF AI TECHNOLOGY AND THE SKILLING, WHICH IS IMPORTANT, TO HAVE PEOPLE READY IN THE CAPABILITY TO LEVERAGE THAT. SO IT IS AS MUCH A PRIORITIZATION OF SKILL, OF TECHNOLOGY WHICH NEEDS TO HAPPEN, AND I THINK ONE THING WE CAN BE CERTAIN IS THE IMPORTANCE OF EMPOWERING HUMAN INGENUITY THROUGH AI. THANK YOU FOR INVITING ME TO JOIN. I AM GIVING IT BACK TO YOU, AZEEM.

AZEEM: I THINK ONE OF THE MOST INTERESTING DIMENSIONS OF THIS IS THE TECHNOLOGY AND HUMAN SKILLS. YOU DESCRIBED THE CIRCLE OF IMPROVEMENT, HOW THE INVESTMENT IN ONE DRIVE CERTAIN PERFORMANCE WHICH DRIVES MORE INVESTMENT. THAT IS A FASCINATING DYNAMIC. I AM CURIOUS TO HEAR FROM OUR EXPERTS PERHAPS STARTING WITH JARNO, ON HOW ORGANIZATIONS MIGHT BE USING AI TO AUGMENT AND UNLOCK THAT INGENUITY THAT IS WITHIN THEIR EMPLOYEE BASE.

JARNO: AT LEAST FOR THE EXPERIENCE WE HAVE HAD WITH CUSTOMERS, WE HAVE INTERACTED WITH, THE MAIN TWIST CURRENTLY SEEMS TO BE MOVING FROM AUTOMATING STUFF LIKE WE HAVE DONE FOR A WHILE NOW, TO AUGMENTING CREATIVE EXPERTS IN R&D AND IMPROVING THE CAPABILITIES OF DECISION-MAKING AND STRATEGIC FUNCTIONS. I THINK THIS REQUIRES AN INNOVATIVE AND BOLD APPROACH TO USING EMERGING TECHNOLOGY, AND I THINK THAT IS A TALL ORDER FOR MANY COMPANIES TO PULL OFF BECAUSE IT TAKES A LOT OF COURAGE AND IT REALLY TAKES A LOT OF INTEREST AND ACTUALLY WANTING TO TRY OUT AI TO MAKE THAT HAPPEN.

AZEEM: THANK YOU. WHAT IS YOUR VISION FROM ROBOVISION?

JONATHAN: IN TERMS OF GETTING PREPARED FOR THIS SO-CALLED SECOND WAVE OF THE COVID-19 CRISIS, WHAT WE SEE IS ESPECIALLY WITH SPECIALISTS LIKE RADIOLOGISTS, EMBRACING THE TECHNOLOGY BIG TIME, REALLY ENABLING THEIR OWN SKILLS, AUGMENTING IT WITH AI TO MEASURE FASTER AND TO GET THIS PATIENT THE RIGHT TREATMENT THEY DESERVE IN TERMS OF THIS CRISIS.

WHAT WE SEE IN MANUFACTURING IS A GREATER SENSITIVITY TO QUALITY CONTROL BECAUSE OF THE HUMAN LOOP, BECAUSE OF SEVERAL RESTRICTIONS IN EUROPEAN COUNTRIES, WE SEE DURING A LOCKDOWN IT IS DIFFICULT TO GET MANUFACTURING GOING. BUT SOMETIMES MANUFACTURING IS REALLY VERY IMPORTANT FOR THE LIFELINES OF SOCIETIES LIKE FRUIT PACKAGING AND SO ON. INSTEAD, YOU NEED THIS QUALITY CONTROL. WE SEE A BIGGER PUSH IN TERMS OF CRISIS, TO EMBRACE AI AT A HIGHER SPEED, AND THESE PRIOR DEALS OF SIX TO 12 MONTHS ARE NOW DEAL CYCLES OF FOUR WEEKS.

ALSO SMART NATIONS, SOCIAL DISTANCING MEASUREMENTS, YOU CAN JUST MEASURE IF PEOPLE ARE COMPLYING TO CERTAIN REGULATIONS OR IF THEY ARE SOFTENING THESE RESTRICTIONS. SO A LOT OF SPEED, AND OTHER EMBRACING OF THESE NEW TECHNOLOGIES IN THESE NEW ECOSYSTEMS.

AZEEM: THANK YOU, JONATHAN. AND SIMON FROM MOTT MACDONALD, THE SAME QUESTION, HOW THE ORGANIZATION IS USING AI TO AUGMENT AND UNLOCK THE INGENUITY OF THEIR EMPLOYEES. THIS AND TO JONATHAN’S ANSWER, HE IS WORKING IN A PURELY SOFTWARE WORLD, AND PERHAPS THE CADENCE IS SLIGHTLY DIFFERENT FROM MOTT MACDONALD, GIVEN THE INFRASTRUCTURE. BUT I’M SURE THERE IS A CONNECTION BETWEEN AI AND THE COMMUNITY OF YOUR TEAMS.

SIMON: THERE ALMOST CERTAINLY IS. AS AN ENGINEER I USED TO HAVE TO SIGN INTO INFRASTRUCTURES AND THEN PUT IT INTO A PRODUCTIVE MODEL WITHIN THE ENGINEERING APPLICATION, AND IT WOULD CONFIRM MY CHOICE. I WOULD TALK WITH A MEMBER ABOUT BEING OVERSTRESSED OR NOT. THEN WE CAN PUT THE SAME INPUTS IN THAT ENGINEERS WOULD GET, AND THE MODEL WILL MAKE A SUGGESTION OF WHAT THE BUILDING INFRASTRUCTURE SHOULD BE. SO THE ENGINEER CAN TAKE IT ON AND INTERPRET IT CORRECTLY. WE ARE SEEING A LOT OF WORK, ALMOST SUBCONSCIOUSLY BEING SUPPORTED BY AI, BEING ASSISTED BY THE MACHINE LEARNING.

ALSO NORMALIZATION, TAKING THE JUMP TO AI BY THE CORTEX, WHICH IS ENHANCING OUR KNOWLEDGE MANAGER WITHIN THE ORGANIZATIONS, WHERE THERE ARE DANGERS OF KNOWLEDGE BEING TRAPPED. IT IS ONE OF THOSE SILENT AI PARTNERS THAT IS HELPING TO CONNECT THE ORGANIZATION AND BRING IT TOGETHER TO HELP US ACHIEVE OUR MISSION.

THE THIRD STRAND WE HAVE BEEN LOOKING AT IS AROUND MAKING INFRASTRUCTURE SMARTER. I KNOW TECHNICALLY IT IS LARGELY INANIMATE OBJECT, SO MAKING IT SMARTER IS PROBABLY A BIT OF A CONTRADICTION THERE. THERE IS SO MUCH DATA AVAILABLE WITH THE ASSETS THAT WE HAVE IN THE WORLD, FROM A RAILWAY STATION TO A ROAD, HOSPITALS, ENTIRE TEAMS. WE HAVE BEEN LOOKING AT USING AI AND HELPING TEAMS WITHIN OUR ORGANIZATION NAVIGATE IT SO THEY CAN ADVISE CLIENTS HOW TO GET ASSETS AND HOW TO BEST USE THEM. WE CAN MODEL MUCH QUICKER THROUGH AI-BASED PREDICTIVE MODELING TO DETERMINE SAFE SWIMMING CONDITIONS. A SAFE SWIM SERVICE DOWN THERE, YOU WILL GO TO THE BEACH AND SEE A SIGN THAT SAYS THE WATER QUALITY IS FIT FOR SWIMMING. WE KNOW THAT THROUGH PREDICTIVE AI MODELING. WE KNOW WHERE THE RUN-OFF IS, WHAT THE LEVELS ARE. ALL THAT INFORMATION WOULD BRING YOU TOGETHER. ALLOWING PEOPLE AS A CONSUMER, IT IS A BIG FOCUS AT THE MOMENT.

AZEEM: ANOTHER IDEA THAT CAME ACROSS IS THE NOTION OF INCREASING SPEED. I WANT TO RAISE THAT QUESTION IN OUR LATER QUESTIONS. I’M CURIOUS ABOUT THIS, TO PUT THIS TO JARNO AND JONATHAN IN PARTICULAR. THIS QUESTION ABOUT WHETHER THE PRIOR INVESTMENT IN EQUIPPING EMPLOYEES TO BE SKILLED AND SUCCESSFUL WITH AI HAS MADE FIRMS MORE AGILE AND RESILIENT. WHICH OF THOSE SKILLS ARE BENEFITING FROM THE MOST. PERHAPS JONATHAN YOU COULD BE THE FIRST TO TAKE THIS ONE.

JONATHAN:  WHAT WE SEE IS THAT COMPANIES EMBRACING AI, HAVE MORE KNOWLEDGE, MORE DIGITALIZATION, AND THIS BRINGS A LOT OF ADVANTAGES. IT BRINGS THE ADVANTAGE OF KNOWING WHAT DISEASES ARE BECAUSE YOU ARE WORKING WITH CAMERAS AND YOU CAN MINE THE DATA, KNOW WHETHER A DISEASE IS MORE PRONE THIS YEAR THAN LAST YEAR. IN THE CONTEXT OF SMART NATIONS YOU CAN KNOW WHAT IS THE DIFFERENCE BETWEEN PEOPLE STREAMS. WHAT WE SEE IS A LOT OF CONTROL. PEOPLE AND ORGANIZATIONS GET CONTROL OF THE FLAWS, THEY ARE AWARE OF QUALITY ISSUES, AWARE OF DIFFERENT KINDS OF ISSUES WITHIN THEIR ORGANIZATION.

AZEEM: THANK YOU. JARNO, HOW ABOUT YOUR PERSPECTIVE ON THE QUESTION? I’D LOVE TO PUT IT TO RALPH AS WELL.

JARNO: INVESTMENT IN ANY EMERGING TECHNOLOGY AND THE DETAILS AND PAINT A BIG PICTURE OF WHERE BUSINESS IS HEADING BECAUSE TECHNOLOGY IS SO EMBEDDED IN BUSINESS TODAY. MACHINE LEARNING IN PARTICULAR, BECAUSE OF THE SET OF POSSIBILITIES THAT CAN SIMULATE A BUSINESS ENVIRONMENT AND SIMULATE DIFFERENT OUTCOMES AND PREDICT IMPOSSIBLES. I THINK THAT CREATES A LOT OF RESILIENCE FOR THE COMPANIES ADOPTING THIS TYPE OF TECHNOLOGY. BUT AT THE SAME TIME, I THINK CREATIVE PROBLEM-SOLVING AND STRATEGIC DESIGN SKILLS WILL BECOME EVEN MORE IMPORTANT BECAUSE MACHINE LEARNING, MOVING FROM DESIGN STUFFED AUGMENTING AND SOLVING PROBLEMS, MOVES IT CLOSER TO ENGINEERING. HUMAN INGENUITY THAT DESIGNED THE STRATEGIC BITS WILL BECOME EVEN MORE IMPORTANT IN TIMES LIKE THESE.

AZEEM: THANK YOU, JARNO. RALPH, I WANTED TO COME TO YOU ON THIS PARTICULAR QUESTION, WHICH IS WHETHER PRIOR INVESTMENT IN EQUIPPING EMPLOYEES WITH SKILLS TO BE SUCCESSFUL WITH AI HAS MADE FIRMS MORE AGILE AND RESILIENT. JARNO ADDED A DETAIL THERE ABOUT STRATEGIC AND CREATIVE PROBLEM-SOLVING AS AN IMPORTANT COMPONENT. DOES THAT REFLECT YOUR EXPERIENCE?

RALPH: I WOULD SAY THAT, YEAH, THEY MAY BE A STEP OR TWO FURTHER AHEAD ON WHAT I’VE SEEN IN THE BROADER MASS USAGE OF AI.  REFLECTING ON CUSTOMER ENGAGEMENTS AND THE FEEDBACK WE’RE GETTING, AND THE THINGS WE ARE SEEING, WHAT CLEARLY MAKES A DIFFERENCE IS RIGHT NOW IS MOST COMPANIES ARE DEEPLY INVESTING INTO DATA-DRIVEN OPERATING MORE FOR THE ORGANIZATION. I SEE THEY MAKE A LOT OF DIFFERENCE NOW. I JUST HAD A CALL JUST YESTERDAY WITH A LUXURY GOODS COMPANY, WHICH IS PRETTY STRESSED IN A GIVEN ENVIRONMENT. BUT THEY HAVE BEEN SO CONFIDENT IN THE DATA MODELS THEY HAVE BEEN BUILDING NOW, HOW THEY ARE FORECASTING AND PREDICTING THE TYPE OF PRODUCT AND REVENUE NUMBERS, AND SEE THE PROGRESS OF ENRICHING THESE DATA MODELS OVER THE LAST WEEKS BY COLLECTING EXTERNALLY, WHERE YOU THINK ABOUT SHOPS OPENING, STARTING AGAIN, SEEING T HOW PEOPLE ARE ALLOWED PHYSICALLY TO GO INTO A SHOP, MULTIPLY THE SHOP SIZE, WITH PEOPLE, BUT YOU CANNOT GO IN THERE. GIVE THEM MUCH MORE CONFIDENCE IN HOW THEY PREDICTED BUSINESS. THAT IS BASED ON PEOPLE INVESTING AND THEN EDUCATING PEOPLE IN BEING REALLY DEEP INTO THIS RESEARCH SIDE. THAT IS COMING STRONG IN MANY COMPANIES IN DIFFERENT SEGMENTS, AND FINANCE, IN MAINTENANCE AND BACK-OFFICE ORGANIZATIONS. THERE IS THIS USAGE HAPPENING THAT WAS INVESTED OVER THE LAST 12 MONTHS, I WOULD SAY.

AZEEM: PROBABLY THE BEST TIME TO PLANT A TREE IS 20 YEARS AGO, AND THE SECOND BEST TIME IS TODAY. I WANT TO BUILD ON THIS IDEA THAT YOU HAVE INTRODUCED HERE, RALPH, WHICH IS THAT OVER THE PAST FEW WEEKS COMPANIES HAVE HAD TO GATHER AS MUCH DATA AS THEY CAN ABOUT THEIR NEW NORMAL. THERE IS THIS IDEA THAT AI SYSTEMS ARE BUILT WITH MODELS THAT ARE AT SOME POINT TRAINED ON THE DATA THAT WE KNOW UP UNTIL THEN, AND THE WORLD HAS CHANGED IN THE LAST SIX WEEKS. I AM CURIOUS TO THIS QUESTION ABOUT HOW FIRMS ENSURE THAT THEIR AI MODELS ADAPT TO THAT NEXT NORMAL. I WOULD BE HAPPY TO ASK JARNO’S VIEW OF THAT FIRST, AND THEN BE HAPPY TO TAKE THAT OF THE OTHER PANELISTS AS WELL.

JARNO: I HAVE HAD A FAIR BIT OF EXPERIENCE ADAPTING MODELS WITH THESE MACHINES. THE PROBLEM WITH MOST MACHINE LEARNING WE SEE TODAY IS IT THE ONLY USES PAST DATA AND DOES NOT EXPLORE THE WORLD AROUND IT. SOME COMPANIES HAVE BENEFITED MASSIVELY FROM USING REINFORCEMENT LEARNING IN A CHANGING ENVIRONMENT. BECAUSE THAT IS A DREAM WORK, NATIVELY ADAPTING TO A CHANGING WORLD IN LET’S SAY DYNAMIC PRICING OR PERSONALIZED NEWCOMERS. OTHER FRAMEWORKS SHOULD BE USABLE, TOO, BUT THE CORE PROBLEM WITH MACHINE LEARNING IS THAT THEY ARE NOT EXPLORING NEW CHOICES, SO WE ARE NOT LEARNING ANYTHING NEW. WE SHOULD NOT JUST EXPLOIT PAST DATA, WE SHOULD ACTUALLY INFECT, STOP SAYING THAT WE NEED DATA FOR AI, BECAUSE IT IS JUST NOT TRUE.

AZEEM: ONE OF YOUR EXAMPLES WAS THAT YOU TRAINED MACHINE VISION SYSTEMS TO RECOGNIZE CT SCANS OF A PATIENT’S COVID LUNGS, WHICH IS A NEW DATA SET THAT DID NOT EXIST THREE MONTHS AGO. WHAT IS YOUR TAKE ABOUT WHAT YOU NEED TO DO TO MAINTAIN THESE MODELS AND KEEP THEM ENSURE THAT THEY ARE READY FOR THE NEXT NORMAL, BOTH THE CURRENT ONE AND THE ONE AFTER THAT?

JONATHAN: BE EXTREMELY FLEXIBLE. IT IS A SIMPLE ANSWER, BUT MAKE SURE THAT THE FLEXIBILITY IS SHORT AND WITH SCALABILITY. WE HAD ALMOST UNLIMITED SCALABILITY SO WE COULD ONBOARD A LOT OF HOSPITALS. WE HAVE DONE THAT ON THE SECOND DAY IN LOCKDOWN. WE HAVE CONTACTED MICROSOFT AND SAID IF YOU WANT ALL OF THESE HOSPITALS UPLOADING DATA IN A PLATFORM, IT IS PERFECTLY FEASIBLE FROM A CLOUD’S POINT OF VIEW. A CLOUD IS MADE FOR THESE KIND OF THINGS, AND YOU NEED TO BE AWARE OF THE SPECIALISTS THEMSELVES, NEED TO HAVE THE RADIOLOGIST IN THIS CASE, TO HAVE A GOOD ENVIRONMENT TO LABEL THIS DATA, SO THAT IT NEEDS TO BE WITH ALL THE TOOLING BECAUSE THEY ARE VERY NEEDED AT THIS MOMENT. THERE IS NO MEDICAL SPECIALIST IN THE FRONT LINE THAT HAS TIME, A LOT OF TIME RIGHT NOW. YOU NEED TO MAYBE BE AWARE THAT IT NEEDS TO BE GENERIC AND VASTLY ADAPTABLE FROM YOUR KIND OF USE CASE. WE HAVE MANAGED TO DO THAT WITH MICROSOFT BY MAKING THE CITY AI MODELS.

AZEEM: SIMON AND RALPH, I AM COMING TO YOU WITH THIS QUESTION AS WELL, BUT I JUST WANT TO PLAY BACK SOMETHING THAT I THINK IS INTERESTING AND WHAT JONATHAN JUST SAID, WHICH IS THAT OF COURSE YOU NEED TO KEEP THE DATA MODELS UP-TO-DATE. PEOPLE WHO HAVE TO DO THAT DO NOT OFTEN HAVE THE TIME TO DO THAT, SO YOU HAVE TO AUGMENT THEM WITH AUTOMATED SYSTEMS. THOSE ARE LEARNING SYSTEMS AS WELL. JONATHAN?

JONATHAN: YOU HAVE TO USE TECHNIQUES LIKE PREDICTIVE LABELING, LIKE GIVING A PROPOSAL TO A RADIOLOGIST DETECTING COVID IN THE LUNG. IT IS SOMETIMES A LENGTHY INSTRUCTION SHEET, AND SOME OF THEM HAVE MISUNDERSTOOD SOME INSTRUCTIONS, SO YOU NEED TO WITH MACHINE LEARNING UNDERSTAND THAT IF SOMEBODY IS LOSING TIME BECAUSE OF INCORRECTLY LABELING, HE IS FILING UP GARBAGE IN, GARBAGE OUT WITHIN THE DEEP LEARNING SYSTEM. YOU NEED ALL KINDS OF TUNING TO MANAGE THE CROWD OF DATA. THIS CROWD CAN BE VERY VERSATILE. WE HAVE PEOPLE FROM SOUTH AFRICA OR VENEZUELA LABELING RECYCLING DATA, BUT WE HAVE SPECIALISTS, RADIOLOGIST LABELING CT DATA. THIS TRULY NEEDS TO BE SO GENERIC THAT YOU CAN SWIFTLY PIVOT YOUR USE CASE ACCORDING TO A CRISIS. YOU UNDERSTAND?

AZEEM: ABSOLUTELY. THAT IS A FANTASTIC CASE STUDY.

 

Part 2

AZEEM: LET ME TAKE THIS QUESTION ABOUT MODELS NOW, AS A REMINDER. IT IS HOW SHOULD FIRMS ENSURE THAT AI MODELS ARE CAPABLE OF ADAPTING TO THIS NEXT NEW NORMAL. AND PERHAPS WE WILL HEAR FROM SIMON FIRST, AND THEN I WILL COME TO RALPH.

SIMON: WHAT IS IMPORTANT WITH MODELS IS THAT THEY DON’T UNDERSTAND PESSIMISM. AT THE MOMENT WE ARE FEEDING THEM RATHER PESSIMISTIC DATA SETS.  WE HAVE TO BE CAREFUL IF WE ARE USING THOSE KINDS OF MODELS THAT WE ARE NOT TRAINING THEM TO BE PESSIMISTIC. SO WHEN THINGS EMERGE AND THINGS ARE BETTER, THEY DO NOT GIVE US THE NEGATIVE OUTCOMES COMES EVERY TIME. THE DATA SET HOW AI IS USED ON MACHINE LEARNING HAS TO BE CONTEXTUAL. THERE NEEDS TO BE A BROAD ENOUGH CHURCH FOR THE RIGHT TO VIEW TO BE FORMED. IT IS REALLY IMPORTANT THAT PEOPLE USING THESE ADAPTIVE MODELS, THAT THEY USE RETROSPECTIVE DATA TO GET SOME POSITIVITY, TO GIVE A BIT OF A SLANT, A BIT OF AN UNDERSTANDING, AND THEN TAKE IT FORWARD. WE ALSO RECOGNIZE THE FACT THAT PROBABLY ALL OF THAT DATA IS AVAILABLE TO YOU, SO PART OF IT IS STRINGING THAT DATA TOGETHER, PUTTING IT INTO A MODEL AND SEE HOW IT REACTS AND HOW IT POPULATES. THAT IS THE SECOND PART OF IT, ESPECIALLY WHEN YOU DO NOT HAVE A MODEL TO START WITH.

AZEEM: YOU STARTED OFF WITH PESSIMISM BUT THEN ENDED UP POSITIVE, I KNOW MANY A SERIES THAT DIED AFTER STRINGING DATA TOGETHER. IT IS ALWAYS A BIG CHALLENGE. RALPH, I’M CURIOUS ABOUT THIS QUESTION ABOUT HOW YOU ENSURE MODELS ADAPT TO THE NEXT NORMAL, AND IN PARTICULAR, THIS SEEMS TO BE  A CASE, AS IT CAME ACROSS FROM SIMON’S ANSWER AND JARNO’S, IT IS A PEOPLE SKILLS, HUMAN CAPITAL QUESTION TO TACKLE.

RALPH: I WOULD SAY IT STARTS WITH THE HUMAN POINT OF VIEW, AND I DON’T KNOW IF IT FITS HERE, BUT THE DATA CENTERS NEED TO BRING A LEVEL OF CHOREOGRAPHY WITH DATA SCIENTISTS NEED TO TRAIN AND REACH OUT FOR DATA. THE REASON I AM SAYING IT THAT WAY IS BECAUSE I THINK THE SHIFT I HAVE SEEN OVER THE LAST SIX MONTHS IS THAT IT STARTED WITH COMPANIES BUILDING MODELS AND INSIGHTS BASED ON THEIR EXISTING DATA. RIGHT NOW, I SEE A PHASE WHERE SOME COMPANIES START OUT TO REACH AND FIND OUT WHAT EXTERNAL DATA IS AVAILABLE, BUT THE PROCESS I WOULD SAY IS ALMOST RANDOM. SO WHAT I AM OBSERVING OVER THE LAST 12 WEEKS IS THAT WE SEE MORE AND MORE COMPANIES COMING IN WITH A SPECIALTY OF DATA SET, WHICH IS AUGMENTING COMPANY-OWNED DATA SETS. SO I SEE A LOT AS AN EXAMPLE IN THE CONTEXT OF SUPPLY CHAIN. THAT HAD AN IMPACT ON COMMERCIAL COMPANIES. I SAW IT HAVING AN IMPACT IN THE HEALTH CARE INDUSTRY. BUT I DON’T SEE GOVERNMENT INSTITUTIONS ASKING SUPPLY CHAIN COMPANIES TO HELP THINK THROUGH HOW THEY ORGANIZE A COUNTRY IN TERMS OF LOGISTICS CAPABILITY. BUT IT NEEDED TO HAVE A STEP IF SOMEBODY GOES OUT OF THE FRAME AND BASICALLY LOOKS AT PARTNERS WHO ARE HAVING A VERY DIFFERENT DATA SET COMPARED TO THEIR EXISTING BUSINESS MODEL, AND JUST TRIED TO COMBINE AND GET THAT PIECE OF DATA ACCESS INTO THE FULL MODEL. SO HAVING IT AS A MODEL, HAVING A HUMAN DRIVER, USING NOW A REAL OUTREACH TO BRING PARTNERS INTO PLAY I THINK IS SUPER IMPORTANT TO FACE WHERE WE ARE RIGHT NOW. I THINK IT IS TRUE, IT IS NOT ABOUT HAVING A DREAM THAT YOU HAVE TO BE A PERFECT AND HOLISTIC DATA SET, BUT IT IS HUMAN ASPIRATION TO REACH OUT AND BRING THE NEXT BEST POTENTIAL SOURCE AND PARTNERSHIP TO THAT MODEL, WHICH I THINK MAKES A DIFFERENCE AS I AM OBSERVING IT RIGHT NOW.

AZEEM: THANK YOU VERY MUCH FOR THIS. THERE IS SO MUCH TO DELVE INTO ON THIS QUESTION, SO PERHAPS WE WILL DO SO LATER ON. I AM CURIOUS TO MOVE TO THE NEXT QUESTION, WHICH IS REALLY ABOUT HOW WE ARE SEEING THE DEPLOYMENT OF AI WITHIN A PARTICULAR BUSINESS FUNCTION? MY OWN EXPERIENCE HAS BEEN THERE WERE CERTAIN BUSINESS FUNCTIONS THAT ARE OFTEN THE FIRST TO BRING THIS TECHNOLOGY ON, BUT THAT IT DOES VARY QUITE A LOT FROM ORGANIZATION TO ORGANIZATION, SOMETIMES DOWN TO INDIVIDUALS WHO SEE THE OPPORTUNITY. I AM VERY CURIOUS ABOUT WHAT YOUR OWN EXPERIENCE IS WITH WHICH BUSINESS FUNCTIONS MIGHT BE LEADING WITH AI, WHILE OTHERS ARE LAGGING. PERHAPS SIMON, YOU WOULD BE SO KIND TO ANSWER THIS FIRST, AND THEN WE WILL GO TO THE OTHER PANELISTS AS WELL.

SIMON: SURE, THE SMART INFRASTRUCTURE TEAM, YOU WOULD EXPECT THEM TO LEAD THE WAY FORWARD. THE REASON WHY WE CREATED IT, TO ENABLE OUR CLIENTS TO MAXIMIZE THEIR INVESTMENTS AND THEIR ASSETS AND BUILD THESE THINGS. THE REASON THAT GROUP IS LEADING IS BECAUSE THEY HAVE GOT AN INTEREST IN IT. IT IS NOT JUST SOMETHING THAT THEY TEND TO DO, THEY HAVE AN INTEREST AND PASSION WITHIN THAT, SO THEY ARE DRIVING IT FORWARD.

THE OTHER PART OF THE ORGANIZATION, TAKING A LEAD IN A DIFFERENT DIRECTION, THEY ARE TAKING REAL ADVANTAGE FROM THAT MACHINE CURATED, MACHINE SUGGESTED KNOWLEDGE AND HELPING THEM TO FORM BETTER TEAMS TO WIN THE RIGHT WORK. THE SIMPLE SORT OF AI INVESTMENTS THEY DID NOT KNOW THEY WERE USING AI, BUT THEY ARE LEADING THE WAY. AND THERE ARE OTHERS. THIS IS A STEP CHANGE. THIS IS A CLASSIC BELL CURVE MOMENT WHERE YOU HAVE THE EARLY ADOPTERS. EVERY ORGANIZATION HAS TO DO SO FOR ALL THE RIGHT REASONS, AND I THINK WE HAVE A GOOD BALANCE.

AZEEM: WE HAVE ABOUT SIX MINUTES LEFT BEFORE WE MOVE TO THE NEXT PHASE OF THIS. THE TIME HAS REALLY GONE WITH THESE WONDERFULLY DEEP ANSWERS. ON THAT QUESTION, WHICH FUNCTIONS DO YOU SEE LEADING. JARNO, WHAT HAVE YOU SEEN ACROSS THE WORK YOU HAVE DONE? OH, I THINK WE HAVE LOST JARNO. JONATHAN, WHAT HAVE YOU SEEN?

JONATHAN: WHAT I HAVE SEEN IS THAT IT IS RELATED TO THE EVOLUTION IN THE AI ITSELF. DEEP LEARNING WAS FOUNDED ON THE PREMISE OF REVERSE ENGINEERING IN THE SYSTEM, AND WHAT WE HAVE SEEN IS THAT BUSINESSES RELATED TO IMAGERY AND THE ANALYSIS OF IMAGERY IS ESSENTIAL. IT IS GOING TO BE ESSENTIAL THAT THEY LEAD BECAUSE IT IS SIMPLE AND IT IS NOT SO RELATED TO BLACK SWAN EVENTS LIKE THE CORONA CRISIS. WHAT IS MUCH MORE DIFFICULT IS THE TIMELINES WITH AI, BECAUSE WE AS HUMAN BEINGS CANNOT EASILY LABEL. WE ARE OFTEN OURSELVES IN STRONG DISCUSSIONS ABOUT IMPLEMENTATION OF TIMELINE. IF THERE IS ONE SINGLE THING WHERE WE MOSTLY AGREE ON, IT IS ON PHYSICAL INFORMATION BECAUSE IT IS CLEAR AND PRESENT AND YOU CAN POINT TO IT AT A GLANCE. SO IT IS VISION FIRST, AND WE SEE A LOT OF EVOLUTION IN THE SPACE. THEN YOU HAVE THE MORE IMMATURE STACKS OF TECHNOLOGY, REINFORCEMENT LEARNING, TIMELINE ANALYSIS, AND CERTAIN DIFFICULT CONTEXTS. THAT IS OUR TAKE ON THE SITUATION.

AZEEM:5 WE JUST GOT JARNO BACK AGAIN. THE EXPERIENCE THAT YOU HAVE SEEN WITH WHICH BUSINESS FUNCTIONS MIGHT BE LEADING WITH AI AND WHICH ONES MIGHT BE LACKING?

JARNO: IT IS CLEAR THAT BUSINESS FUNCTIONS THAT HAVE A FIRST FEEDBACK LOOP ARE SORT OF TRIUMPHING IN THIS TYPE OF CAREER BECAUSE THEY CAN SORT OF EXPORT TECHNOLOGIES FASTER BECAUSE THEY CAN TRY OUT NEW THINGS WITH CERTAINTY, KNOWING WHO THEY WORK ON OR NOT. KNOWING IF THEY WORK OR NOT. USING THAT IN R&D WITH THE STRATEGIC FUNCTIONS. THE FEEDBACK LOOP IS PRETTY LONG AND IT TAKES A WHILE TO KNOW IF SOMETHING WORKS OR NOT. SO I THINK THAT AFFECTS THE ADOPTION RATE ACROSS DIFFERENT BUSINESS FUNCTIONS. YOU CAN EASILY SEE THAT SORT OF FEAR OF ADAPTING NEW TECHNOLOGY. LIKE IN THE WHISKY CASE WHERE YOU CAN IMAGINE WHEN PEOPLE IN SCOTLAND HEARD THAT WE ARE GOING TO MAKE WHISKY WITH COMPUTERS. IT WAS LIKE NOTHING THEY HAD EVER SEEN AND HEARD, AND WE HAVE GOTTEN FEEDBACK THAT YOU CANNOT DO THIS STUFF. A WEEK AGO, WE WON A REALLY PRESTIGIOUS PRIZE ON AN AWARDS SHOW FROM THE INTELLIGENCE WHISKY. I KNOW THAT FUNCTIONS THAT HAVE LONG FEEDBACK LOOPS ARE GOING TO BE A BIT BEHIND.

AZEEM: THANK YOU FOR THAT. I CAN TELL YOU THAT THE EMPTY BOTTLE OF YOUR WHISKY THAT I HAVE SITTING ON A SHELF IN A KITCHEN IS TESTAMENT TO THE FACT THAT THE AI IS WORKING THERE. WE HAVE 3, 4 MINUTES LEFT BEFORE WE MOVE TO AUDIENCE QUESTIONS. WE HAVE THE LAST QUESTION, AND I WILL START WITH JONATHAN FIRST. WHAT BRIEF ADVICE DO AI-LEADING BUSINESSES HAVE FOR OTHERS THAT ARE NOT AS FAR ALONG THAT JOURNEY AS THEY MIGHT BE? IF WE COULD START WITH JONATHAN, PLEASE.

JONATHAN: START EARLY AND ACCEPT TO FAIL FAST. THE INNOVATION GOES INTO A FAST ITERATION AND YOU HAVE GONE INTO EFFECTS AND MVPS QUICKLY. DO NOT FALL INTO THE TRAP OF ANALYSIS PARALYSIS AND OVERANALYZE. JUST JUMP INTO IT AND GET IT GOING, GET THE ABSORPTION GOING IN YOUR ORGANIZATION BECAUSE YOU WILL SEE OTHER THINGS WITH PURE AI, YOU WILL SEE THAT YOUR DATA IS NOT CONSISTENT OVERALL, AND YOU WILL SEE PRACTICAL ISSUES BEFORE YOU CAN REALLY START THIS WONDERFUL JOURNEY OF CREATING THE MOST OUT OF YOUR CONTEXT. THE OTHER THING IS REALIZE THAT IF YOU WAIT TOO LONG, YOUR COMPETITOR WILL PROBABLY GRAB SOME MARKETS AND YOU WILL BE TOO LATE AT SOME POINT. IF WE ARE LIVING IN FAST-MOVING TIMES, DISRUPTIONS, IT IS IMPORTANT TO JUMP ON THE WAGON.

AZEEM: WAGONS AND WHISKY. NOW I’M GETTING CONFUSED. LET’S ASK JARNO THAT SIMILAR QUESTION. WHAT ADVICE WOULD YOU HAVE FOR COMPANIES THAT ARE LESS FAR ALONG THERE AT OUR JOURNEY?

JARNO: I THINK THAT IS A GOOD AND REALLY IMPORTANT QUESTION, AND I THINK IT SORT OF BOILS DOWN TO THE HUMAN BITS AND THE CULTURE BITS, THAT WE SHOULD NOT BE AFRAID OF USING EMERGING TECHNOLOGY AND AUGMENTING BECAUSE IT IS NOT REALLY ABOUT LOSING CONTROL, BUT IMPROVING OUR OWN DECISION-MAKING. I THINK ALSO WE SHOULD OPT FOR USING APPROACHES WHERE MACHINES ACTUALLY LEARN AND GENERATE SOMETHING, AND EXPLORE WHAT IS POSSIBLE INSTEAD OF REPEATING WHAT WE ALREADY KNOW, WHEREVER THAT TYPE OF EXPLORATION IS POSSIBLE. I THINK YOU WILL BE SURPRISED.

AZEEM: THANK YOU. SIMON, I AM CURIOUS TO HEAR FROM YOU, IN PARTICULAR BECAUSE YOUR SECTOR IS ONE THAT HAS LONG FEEDBACK LOOPS. WHAT ADVICE WOULD YOU HAVE FOR ORGANIZATIONS THAT ARE LESS FAR AHEAD ON THAT JOURNEY?

SIMON: OUR FEEDBACK LOOPS ARE USUALLY MEASURED IN DECADES. SO FIRST, IT IS REALLY AROUND CONFIDENCE AND TRUST AND WHAT IT IS DOING. IF YOU HAVE NOT ENGAGED WITH AI BEFORE, DIPPING YOUR TOE IN, IT IS ABOUT GAINING CONFIDENCE AND TRUST WITH WHAT THE ANSWERS AND WHAT THE IMPLICATIONS ARE. THE OTHER POINTS, YOU DO NEED TO APPRECIATE THAT IT IS NOT YOUR SILVER BULLET. IT IS NOT GOING TO GIVE YOU THAT 4:00 A.M. EPIPHANY STRAIGHTAWAY. BUT GETTING YOUR DATA IN ORDER, SOMETIMES IT IS A PAINFUL PROCESS, BUT IT HELPS YOU GET THINGS A BIT CLEANER, STANDARD FORMAT. IN OUR INDUSTRY, WE ARE QUITE LUCKY. WE ARE 10 YEARS INTO A STANDARD CYCLE, AND WITHIN THE STANDARD CYCLE, THEY HAVE BEEN STARTING TO PRESCRIBE THE METADATA THAT YOU SHOULD BE CAPTURING WITHIN THE CREATION OF YOUR ASSETS. SO THEY ARE REACHING QUITE FAR AHEAD. I WANT TO STRESS THAT YOU HAVE TO BE MORE ECONOMICAL WITH DATA, COLLABORATE A BIT MORE. JUST GO FOR IT.

AZEEM: RALPH, LET’S PUT THIS LAST QUESTION TO YOU AGAIN, WHICH IS ABOUT THE ADVICE YOU WOULD GIVE TO CLIENTS WHO ARE NOT AS FAR ALONG THEIR AI JOURNEY AS SOME OF THE FIRMS WE HAVE BEEN DISCUSSING SO FAR IN OUR SESSION.

RALPH: I WOULD REFRAME IT AS OBSERVATIONS I HAVE BEEN ABLE TO TAKE FROM COMPANIES. FOR ME, ALWAYS A STARTING POINT IS STUDIES WOULD SAY TWO YEARS DOWN THE ROAD, 60% TO 65% OF OUR GDP IS FROM A DIGITAL FOOTPRINT. BY DEFINITION OF LEADERSHIP, A COUNTRY SHOULD HAVE A DIGITAL TECHNOLOGY AGENDA.

HAVING LEADERSHIP THAT CAN ARTICULATE WHAT AI WILL DO FOR A COMPANY MAKES A BIG DIFFERENCE. LEADERSHIP ON AI I THINK DRIVES BEHAVIOR. BY DOING SO, MANY PEOPLE ACTUALLY FIND OUT THAT OF ALL OF THE THINGS AND EXPERIENCES THEY HAVE, IT IS ALREADY AUGMENTING DAILY LIFE. ON THE PRIVATE PERSONAL SIDE AS MUCH AS IN BUSINESS. THE NEXT STEP HAS ALWAYS BEEN FOR ME THAT PEOPLE START HAVING BOARD MEETINGS BASED ON DATA AND NOT BASED ON PRESENTATIONS. SO WHEN YOU START HAVING EXECUTIVES LOOKING AT DATA WHICH IS REAL-TIME PULLED, WHICH IS REASONABLY DONE, AT THE MOMENT THEY HAVE THE DATA, THEY SAY WHAT MORE CAN YOU GET OUT OF IT? HOW CAN YOU USE IT BETTER? THAT HAS BEEN TO ME ALWAYS THE BEST WAYS TO ACCELERATE. AND BUILD GROUPS OF KNOWLEDGE. INVEST IN SKILL SET OF PEOPLE. DO RESEARCH WORK. ON THE PRODUCTION SIDE, PEOPLE WHO AUGMENT VIDEO TECHNOLOGY, JUST BUILDING GROUPS OF KNOWLEDGE AND DATA-DRIVEN SKILLS, THAT HAS ALWAYS BEEN THE RECIPE FOR SUCCESS. FROM THERE ONWARDS, I WOULD SAY THAT ALL COMPANIES I HAVE OBSERVED IT, IT IS JUST A SELF-FULFILLING PROCESS OF GROWTH AND INTEREST AND MORE DEPTH WHERE PEOPLE ARE GOING TO USE THE TECHNOLOGY FOR THEIR OWN BENEFIT AND BRINGING PEOPLE AND TECHNOLOGY TOGETHER.

AZEEM: WHEN WE TALK ABOUT PEOPLE AND TECHNOLOGY, THAT TAKES US TO THE QUESTION OF CULTURE. WE DO JUST HAVE FIVE MINUTES LEFT TO ASK ABOUT THIS, EXPLORE THIS QUESTION OF CULTURE. I AM CURIOUS IN PARTICULAR ABOUT THE DISTINCTION OF WHETHER THIS IS SOMETHING THAT HAS TO BE DRIVEN FROM THE TOP DOWN, WHETHER IT CAN HAPPEN FROM THE BOTTOM UP, AND WHAT ARE THE KEY ELEMENTS OF CULTURAL HYGIENE THAT ARE IMPORTANT FOR SUCCESSFUL AI IN SKILLING INITIATIVES. I AM COGNIZANT THAT OUR ATTENDEES ARE APPROACHING THE TOP OF THE HOUR. IF YOU COULD EACH TRY TO ANSWER THIS WITHIN A MINUTE SO WE GET A MOMENT TO SUMMARIZE, THAT WOULD BE GREAT. I WILL ASK JARNO TO START ON THAT QUESTION. THANK YOU.

JARNO: I THINK, LIKE, IN TERMS OF CULTURE, LIKE FOR MACHINES WITH LEARNING, YOU NEED TO BRING THE VALUE FOR THE SORT OF CXO LEVEL, THE SORT OF BOTTOM LEVEL WHERE YOU WANT TO APPLY THAT CHANGE. LIKE IF YOU START AN ENDEAVOR TO DO SOMETHING FOR CUSTOMER SERVICE, YOU NEED TO START WHERE YOU KNOW THE BUSINESS PROBLEM, BUT YOU NEED TO START WITH A CULTURAL APPROACH THAT TAKES THE CUSTOMER SERVICE LIKE REALLY INTO THE LOOP OF DEVELOPING THE ENTIRE SYSTEM AND DOES THAT WITH THAT HUMAN INTELLECT, REALLY HEAVILY ENTWINED WITH WHAT YOU ARE TRYING TO ACCOMPLISH WITH TECHNOLOGY. SO I THINK A LOT OF IT BOILS DOWN TO JUST HOW CAN YOU BUILD THAT TYPE OF EMERGING TECHNOLOGY TO A COMPANY WITH PROJECTS THAT ARE LED AND SORT OF MANAGED FROM THE SORT OF END USER AND FROM THE END USER EXPERIENCE ONWARDS. I THINK THAT WILL LEAD TO A LOT OF SUCCESS.

AZEEM: THANK YOU. WE WILL GO OVER TO SIMON ON THIS, WHICH IS WHAT ROLE DOES COMPANY CULTURE PLAY IN A SUCCESSFUL AI AND SKILLING INITIATIVE? YOU HAVE JUST ONE MINUTE.

SIMON: TOP-DOWN SUPPORT HELPS GET THINGS DONE, BUT WHATEVER YOU DO, FACILITATE THE COALESCING OF LIKE-MINDED PEOPLE TOGETHER. THAT IS THE FIRST POINT. IT DOESN’T MATTER WHERE THEY ARE FROM, JUST GIVE THEM THE PLATFORM OR A WAY OF COALESCING TOGETHER. YOU GIVE THEM THE OPPORTUNITY TO PLAY WITH THE TOOLS AND THE ARTIFACTS AND LET THEM EXPLORE. WE LEARN THROUGH PLAYING THAT THAT IS THE BEST WAY TO GROW AND DEVELOP OUR SKILLS. SHOW A BIT OF EMPATHY TOWARD THEM. THEY ARE LEARNING SOMETHING NEW, PLAYING WITH SOMETHING NEW, PROBABLY ON THEIR OWN TIME, TOO. INCUBATE, EXPAND, AND THEN YOU CAN DEPLOY.

AZEEM: I LOVE THAT. THAT’S GREAT. JONATHAN, YOUR PERSPECTIVE. 45 SECONDS IS NOW YOUR ALLOCATED SLOT.

JONATHAN: ENABLING, ENABLING, ENABLING. ENABLING YOUR CUSTOMER, ENABLING YOUR TEAM. ENABLING FROM A CEILING POINT OF VIEW. LET THEM READ PAPERS, LET THEM CONNECT THE DOTS IN A CREATIVE WAY. DRAW OUTSIDE OF THE BOX. DO NOT BE TOO SCHEMATIC. THAT THEY PLAY AROUND. AS SIMON SAYS, IT IS IMPORTANT NOT TO TRY TO MANAGE IT. THESE SMART PEOPLE, THEY CAN MANAGE THEMSELVES. IT IS A BIT LIKE ANARCHY IN A GOOD WAY. YOU NEED TO HAVE IT WORK AT GRASSROOTS, YOU NEED TO ENABLE IT. GIVE THEM THE TOOLS THEY NEED, THE GPU, A LAPTOP, AND OFF THEY GO.

AZEEM: “ANARCHY BUT IN A GOOD WAY.” RALPH, WHAT ROLE DOES CULTURE PLAY IN AI AND SKILLING INITIATIVES?

RALPH: ESTABLISH A FRAMEWORK, ESTABLISH A FRAMEWORK OF LEARNING, AND MAKE SURE PEOPLE UNDERSTAND IT IS A TECHNICAL ENVIRONMENT. BUT IT IS NOTHING WHICH IS LIMITED TO PEOPLE WITH A TECHNICAL BACKGROUND. SO EVERYBODY IN THE CONTEXT OF AI WITH TOOLS AND THE WAY THAT STUFF IS DONE AND ACTUALLY BENEFIT BY USING SMALL BITS AND PIECES AND JUST GET INTO IT, AND IT MAKES A HUGE DIFFERENCE FOR THE WHOLE ORGANIZATION OF THE COMPANY.

AZEEM: RALPH, THANK YOU FOR THAT, AND THANK YOU TO ALL OF THE PANELISTS. IT IS AN INCREDIBLY RICH DISCUSSION. I HOPE THIS IS BEING RECORDED AND PEOPLE GET A CHANCE TO WATCH IT AGAIN BECAUSE THERE IS SO MUCH NUANCE AND INSIGHT THAT HAS BEEN BROUGHT UP TODAY. THANK YOU VERY MUCH TO JARNO, TO SIMON, JONATHAN, AND FINALLY TO RALPH.



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