Cleve Gibbon

content management, content modelling, digital ecosystems, technology evangelist.

Digital Task-Based Workforce

A successful company will at start the day with valuable information.  After completing a bunch of tasks, that company ends the day with even more valuable information.  And from valuable information comes profit and growth.

Today, the digital workforce is growing to take on more connected and complex tasks. And with knowledge workers are applying artificial intelligence (AI) and intelligent automation (IA), or AiA, to complete tasks in their day to day, digital task-based workforce is growing at exponential rates.

Digital Task-Based Workforce

Task is the unit of work

So envision a workforce where the majority of tasks are digital. A massive ecosystem of small to medium sized connected tasks. Traditionally, knowledge workers spearheaded these tasks. It is their job to complete these tasks by leveraging their expertise across various domains. However, as AiA capabilities grow, this workload is being shared. The digital workforce is morphing into a landscape with a harmonious blend of human intellect and machine efficiency. This partnership has not only accelerated task completion by the digital workforce but also introduced innovative solutions to complex challenges.

Looking ahead to AI Agents

Within a task-based workforce, distinguishing between tasks completed by humans or machines becomes less relevant. But AiA enabled humans are the next first important step towards this reality. That requires people to get comfortable working with AI agents now. And the curious will lead the way.

As the digital workforce matures, humans will cede more control to AI agents. Trusting them with more and more tasks and shifting into a partnering relationships with smart capable AI agents with experience and expertise under their belt. And of course, in some cases the AI agents will lead with humans in support. We’re not there yet, but it’s only a matter of time, and only for jobs we’d consider simple fit for machines. But for now, test ahead, and start learning how AI agents can help you in your day to day.

Knowledge Workers in the AI Age

Knowledge workers use their intellectual skills to create, process, and share information. Scientists, architects, engineers, lawyers, teachers, analysts, planners, and software developers are just a few examples of knowledge workers that think for a living.  They are key contributors to innovation and problem-solving in various industries, leveraging their expertise to drive decisions and strategies.

However, the role and responsibilities of knowledge workers is evolving fast with the accelerated adoption of artificial intelligence (AI) and intelligent automation (IA) – AiA – into future digital workforce.

We’ve heard that 50% of knowledge workers have used AiA in some form or other, directly or indirectly. Moreover, that number increases to over 90% within marketing and advertising.  Interestingly, this usage is not driven by corporate policy.  It’s more self-taught and home schooled.  Nevertheless, AiA usage is on the rise.

Knowledge Workers in Marketing and Advertising

marketing knowledge worker

In marketing, knowledge workers craft messages that resonate with audiences for advertising outcomes. These creatives, from copywriters and designers to strategists and analysts, harness their expertise to develop campaigns that captivate and persuade. As the intelligence age advances, AiA is transforming knowledge worker roles and responsibilities, amplifying creativity and efficiency.

Let’s be clear here, AiA’s influence is profound across the end-2-end creative process.  We are automating routine tasks. Prioritizing the best use cases for specific AI tools from analyzing consumer data and predicting trends to generating intelligent outputs to inform targeted marketing strategies. This enables marketers to craft personalized campaigns that speak directly to individual preferences, significantly enhancing engagement and conversion rates.

Now an advertising agency might employ AI to generate multiple versions of an advertisement, each tailored to different audience segments based on online behavior and preferences. But that’s a lot of additional content.  However, the ambition is to streamline the creative process so that each ad variation is optimized for maximum impact.  It also shifts the certain responsibilities of knowledge workers from creator to curator in the creative process.  And all this what-if ad impact analysis is done at design time, before the ad is activated, if at all.  Yet again adding review and approve responsibilities to the knowledge worker. 

And AiA adoption is not a given

Adoption is critical for sustainable change.  HR departments are in the people trenches fielding the inevitable structural changes to digital workforce of the future. Here are a couple of major and minor organizational AI trends:

Major TrendMinor Trend
Investment increasingConfidence in right AiA investment bets
Likelihood of people replacementEmployee support for change
Workforce transformationExpertise for transformation

Basically, you hear a lot noise about the major trends and less about the minor trends. However, we need to pay more attention to the minors to bring favorable outcomes for the majors, increasing AiA adoption across the organization.

What is AiA

I’ve always been interested in getting things done (GTD). Both professionally and personally. Being productive with a focus on the execution side is important, but not without embracing the rise of intelligence in the workplace.

Right now, Intelligent Automation (IA) has my professional focus.  To drive better client outcomes by supporting knowledge workers you must bring that right blend of methodology and technology.  And you guessed it, AI is that technology making the difference today.  AI amplifies the impact of IA.  AiA, the synergy of AI and IA has intelligence at the center of everything.

    

The Rise of the Digital Workforce

The digital workforce is predominantly made up of human workers. However, AiA will add more and more automated processes, increasing the size of digital workforce.  But more importantly, the shape and structure of the digital workforce will change significantly and permanently.  And the role of humans within the digital workforce will be even more critical.  We have officially entered the future of work discovery phase.  No one knows what that digitial workforce mix will be.  We are all learning together.

However, ignorance is no excuse.  What we do know is that intelligent knowledge workers, those that can work with AiA, will have more opportunities within the shifting and growing digital workforce, than those that can’t. 

AiA gifts knowledge workers with time to perform more human-centric tasks.  By delegating the manual and mundane to machines, we can embrace the creative and innovative to drive intelligent outcomes for others. 

So, where are we today?

Every business is different.  Culture, strategy, talent, operations, innovation, data, technology, just to name a few, and their inter-dependencies, define an organization.

However, the race is to digitize everything, everywhere, all at once, and intelligently.   Do you know what you do?  Are your processes undocumented, documented, automated, and/or integrated?  What’s your mix? Is your scope internal, external, with or without partners? And your data, who owns it?  How do you share, secure, syndicate, sanitize, and simplify it?  Do you know how to monetize what you have?  Have you separated what you sell from effort required to deliver it?

There are just a few questions to address before you can scale your business with AiA.

And the next step is…

Shared awareness.  We are in the intelligence revolution. Steam, mass production, and digital are industrial revolutions that have been and gone.  Now the transformation towards intelligent connected systems, fueled by data, powered by machines, and directed by humans is in full swing. Our forward-thinking leaders are placing big bets in AiA with the clear understanding that the intelligence landscape is critical to future growth and survival.

So, empowered execution follows shared awareness.  Those at the tip of shift have started executing, but not underestimate the amount of effort it requires to reach shared awareness.  And that’s where most of us are playing now.

Help writing help documentation

Creating help documentation is a skill. It is usually not one that is done well by those responsible for building the solution. But you can get help writing help documentation. I recently discovered Synthesia and Scribe, two AI solutions that make the creation of help docs easier. 

Enter Synthesia 

Synthesia

Who doesn’t like video? Synthesia makes it super simple to create help documentation using its library of avatars. Just pick an avatar, enter text in the language of your choosing, and have it speak to your solution. Then generate, share the video, and your done! 

Enter Scribe 

I love Scribe. Just hit the generate button and it will capture how you move about the screen. It’s smart, automatically creating how-to guides. Saving you the hassle of screenshots, annotating them, and then assembling them. Scribe shortens the distance between creation to curation for documentation.  

Into 2024 with technology, workloads, and AI

As the calendar flipped to 2024, I found myself wanting more. After a transformative decade at WPP. A period marked by growth, learning, and remarkable achievements. I decided it was time for a change. This decision wasn’t made lightly. It was the culmination of introspection and a desire for new challenges. Thus, I bid farewell to WPP and took a well-deserved sabbatical to recharge and refocus. I’m now at Omnicom with a focus on technology, workloads and AI.

WPP

My journey with WPP started with a bang in Apr 2014. Our company, Cognifide, was acquired by WPP under the Wunderman OpCo. Wunderman was undergoing massive digital transformation. Cognifide’s role within WPP was to build owned experience platforms for its clients. Many clients. Ford, Investec, ColPal, EY, HSBC, Dell, Herman Miller, Coutts, Barclays, Unilever, Shell, etc. We delivered hundreds of digital platforms during my time at WPP. Then Wunderman became Wunderman Thompson after it merged with JWT, and now it’s VML. I left WPP after a couple of years of leading technology back into The Coca-Cola Company.

So what changed?

Me. After graduating from Oxford University in 2023 with a Master’s in AI for Business, the world looked very different. Something unlocked in me. Like many others, I believe that AI is mission-critical to businesses and people. But it was more than using AI, which is just technology. I’m curious about the operationalization of AI across the organization and equally its widespread adoption. What are the better business outcomes that an intelligent enterprise can deliver at scale, with speed, and sustainably? There’s so much going on. Understanding workloads, standardization of approaches, automating where appropriate, leveraging AI, and tying everything back to results has my full attention.

Omnicom

So, I joined Omnicom in 2023. They have a clear mission, with key partners like Microsoft, and have invested in an AI-driven future. Now I’m part of a technology team helping to accelerate Omnicom towards that future reality.

What’s next?

Focus and execute. Listen and learn. Collaborate and communicate. And above all else, keep moving forward into 2024.

6D Framework for AI

I’m a big fan of Peter Diamandis’s 6D framework used to describe the exponential growth and impact of emerging technologies.  It depicts how technology moves from ’emerging’ to ’emerged’.

The rate of technological change starts with digital and moves deceptively slowly under the radar until its true disruptive impact becomes clear to the few. Once established, the technology dramatically accelerates along an exponential growth path getting cheaper (demonetized), smaller (dematerialized), and accessible (democratized) to the masses. Think iPhones, 5G, the Internet, and now AI.

Singularity University

Back in May 2017, I spent a week at NASA with 30 other business and technology leaders, many of which oversee $1 billion revenue companies.  Peter Diamandis ran a series of future-forward technology lectures as part of his Singularity University program to share the collective current state, provoke discussions with divergent audiences, to change our collective thinking.  He succeeded. 

Singularity University

Now AI was high up on the agenda.  We had luminaries such as Ray Kurzweil sharing his predictions on the future of human-machine integration. 

6D Framework for AI

Now let’s position AI within that 6D framework.  It’s literally been 6 years since I attended Singularity University and our 2017 AI predictions are bang on target.

AI used to be costly, but now it’s more affordable. Smaller versions of huge language models focus on specific problems, and we’re seeing these models targeting web and mobile devices. And of course, everyone has access to AI now.

Every day, we humans are adapting to AI. Governments and corporates alike are navigating the challenges of ethical, responsible, and unbiased solutions as part of creating an acceptable AI code of conduct. Nobody wants an existential crisis.

And finally, talent. Augmented humans, or people comfortable with AI, have an advantage. The workforce is changing fast, especially for non-augmented individuals. Companies are proactively replacing future roles with AI solutions, both led and managed by experienced, AI-adept individuals. Nobody knows what the future talent mix will be, but it will be different.

Wrapping up, that 6D framework shows us that AI is no longer a technology of the future; it’s here now. So, what will you do with it?

Artificial Intelligence and Intelligent Automation (AiA)

Artificial Intelligence and Intelligent Automation (AiA) are connected by intelligence.  And it’s no coincidence.  

Artificial Intelligence and Intelligent Automation.

(Intelligent) Automation

The corporate ask of automation remains the same; do more with less.  Because time is money. Automation is an efficiency play to do things right. Map out the processes that people follow to get things done. Then, start automating the simple tasks to free up increasing amounts of time to do things better suited for humans.  

What we really want is for people to adopt more automation, adapt their current ways of working, to ultimately readily embrace machines as part of their everyday.  Let’s be clear, augmented humans are (going to be) more productive than non-augmented ones.  The future of work is less about (wo)man being replaced by machines, but more about augmented humans displacing non-augmented ones.  This is why workers that ignore what’s happening today do so that their risk, and will more likely end up on the wrong side of the change equation.  

Automation doesn’t create much.  It optimizes a lot.  Intelligent automation uses AI to learn how to automate repetitive and routine tasks.  

Artificial (Intelligence)

AI is the technology that enables machines to perform tasks that typically require human intelligence.  AI is an effectiveness play to do the right things. Machines run algorithms that analyze data, find patterns in it, and make predictions off it.  Today, AI makes routine predictions that need humans to make those last-mile decisions.  You must’ve terms like keeping the human in the loop. Humans still provide the necessary guardrails on decision-making and learning goals to continuously progress machines gain more and more human intelligence.  

However, machines are learning faster than humans in specific contexts.  Once trained, AI required less data, in new contexts, to make accurate predictions.  AI is accelerating toward machine intelligence.

Smarter Children

So, what if as a parent you knew that your child was going to be so much smarter than you ever could be? Not only that but your child’s intelligence could potentially periodically double ad infinitum.   What would you do?  And how would you do it? 

As a civilization, we have struggled to manage the human race with many amazing leaps and near-disastrous events along the way.  We are adding machines into the mix and are re-writing new rules of engagement.  I hope we do better than the Titans and Olympians, where Zeus and his siblings overthrew their parents. Humans are not Titans, and machines are not Olympians. However, we are going to have to work hard to co-exist and deftly sidestep the fall of the Titans (read as humanity)!

The Rise of AI

Over the last couple of years, the rise of AI has been insane. Most definitely within the tech and data world, but more importantly now by users. So let’s be clear, AI is out there. Accessible. Available. Always on.

Before, AI was lurking beneath the surface. Working behind the scenes supercharging the business platforms that platform businesses use to:

  • Spotify; better matches listeners with artists
  • Airbnb; better find the best places to stay
  • Uber; better get you to where you need to be
  • Netflix; better know what to watch next
  • Amazon; better suggest what to buy

Because with AI we can have better business outcomes. But what accelerated things so dramatically, and so publicly. Well, the entire contents of the internet were compressed into an accessible, available, always-on service that you can have a conversation with it. We call this ChatGPT and it marks the arrival of AI for the masses. The game has changed forever.

So, over the last couple of years I’ve been grappling with the true disruptive impact AI will have on business. And in April 2023 I graduated from Oxford University with a Diploma in AI for Business. The timing could not have been better. I have so much to be thankful for and people to thank.

So I’m going to do just that by gently unpacking AI. I’m going to cut through the hype, and add back some context, and have some fun with the rise of AI! But to kick off the thanks, first to the wicked smart AI for Business professors at Oxford University, and most importantly to my wife for giving me to space to grow. Thank you all!

Three Steps to Innovation

We all know innovation is important. But in uncertain economic times, innovation becomes urgent. Innovation is a differentiator tied to future growth and long-term value creation.  There is no faking it here.  You won’t get the results and will lose. But there are simple three steps to innovation you should know to help you make it.

I’m always listening out for the different ways people approach innovation and get results.  I subscribe to Inside the Strategy Room, a McKinsey podcast and stumbled across an episode on taking the fear out of innovation.  This post is an extension of that conversation. Let’s dig in.

What are the three steps to innovation?

Innovation is the practice of:

  1. Finding the right problem to solve 
  2. Identifying the right technology to solve that problem 
  3. Fitting the right business model to scale the solution

Re-look at those three steps to innovation.  They are connected. A subtle shift from problem to solution. Although enumerated in a linear fashion, innovation tends to cycle a few times around these steps to get there. 

What are the innovation outputs?

But don’t stop there. What about the outputs at every step of the way? Think about:

  1. Find the problem 
  2. Identify the solution
  3. Fit the business model

You need to be clear on all three of these outputs to deliver true innovation: problem, solution, and business model.  Each output should have standard format and vocabulary for expressing them for all participants in your innovation ecosystem. Simple to say, hard to execute.  

What are the innovation practices?

Lastly, let’s focus on the innovation practices. This is the hard part. The practices differentiates good from great innovations:

  1. Find the problem
  2. Identify the solution
  3. Fit the business model

How do you find problems, identify solutions, and fit them into business models that work .  This takes both experience and expertise doing innovation. Getting results and learning from them. Really doing the do, where practice makes progress.  Every person, team, company, brand, or organization, does this differently. Driven by culture, access to talent, and leadership. And this is where innovation happens.

Just be clear on where your strengths and weaknesses lie today.  Leverage strengths now and improve weaknesses over time. 

Why what we make matters

Before I leave, the presenters on the podcast said something else about innovation that resonated with me: 

  • We make originals so that we don’t go creatively bankrupt
  • We make sequels so that we don’t go commercially bankrupt

So we need to do both.  However like any industry, sequels/duplicates/reruns are common, some truly exceptional.  But originals are timeless classic.  Don’t be fooled. They are not the same.

Innovation is about improvement and tends to fall in the sequels category.  Innovation is about percentage gains. True originals are inventions.  They require different approaches that result in new business models, new technologies, and new problems to solve.  Inventions are moonshot gains. So when defining success with your teams, with your three steps to innovation, consider which parts above are relevant for you.

Automate today

The promise of automation is to lighten your current load.  To give you more time to focus on the things that matter most.  However, you have to give up precious time now to get more time later.  For already time poor, busy people, that’s just too much for them to automate today. 

The tomorrow never comes syndrome is everywhere.  For companies, we see them tripping over short term revenue wants when struggling to meet long term value needs.  Or at home, sacrificing retirement investments to literally survive today.  

But you have to make a call. And it’s your call.  Do you want to be in the same place next year, or somewhere else?  If the latter, then invest the time.  Automation is supposed to make things better in the long run.  However, we don’t know how much better.  So we hesitate, and many never take that essential first step towards progress.  It’s time to get out of your own way.

Automate today example

I’ve been a long time user of Things.  It’s a task-based tool that runs across all my Apple devices.  I never forget stuff because Things remembers and reminds me.  It’s by task brain. This weekend I got notification that Things had integrated with Apple Shortcuts to better automate tasks.  I was excited at first, and then sighed. But instead of parking the task and kicking that learning downstream, I took the time to educate myself today. 

After a couple of hours of reading and testing, I had converted my micro tasks into macro actions. This equates to a 30 minute saving every day.  That was definitely worth the two hours upfront investment time. I gambled and won.

The automation returns for organisations are literally off the scale.  But you have to give to get. Don’t believe that tomorrow never comes.  It always does.  And when it does, be better than the day before.  Otherwise, what are you doing? 

About Cleve Gibbon



Hey, I’m Cleve and I love technology. A former academic that moved into fintech to build trading platforms for investment banks. 20 years ago I switched to marketing and advertising. I joined a content technology spin-off from the Publicis network that was bought by WPP in 2014. I'm now at Omnicom. These pages chronicle a few of things I've learnt along the way…


My out-of-date cv tells you my past, linked in shares my professional network and on twitter you can find out what I'm currently up to.