Cleve Gibbon

We are rapidly accelerating toward a world of intelligent systems. The stepping stones to intelligence are clear:

• Data: It is the fuel, creating information from which we can glean insights and generate ideas.
• Digitisation: Provides ubiquitous access to everything, everywhere.
• Platforms: Facilitate scaled interactions between producers and consumers.
• Language: Offers a common vocabulary for communication across the enterprise.
• Intelligence for the Masses: Increases the amount of and access to intelligence.

Each of these stepping stones to intelligence represents a paradigm shift. They have been progressing rapidly and independently, converging toward an intelligence-powered future.

Data

Data, derived from the Latin word datum, means something given. Brands enhance their experiences to increase customer interactions, collecting data as a result. This data is the fuel for future growth; the more you have, the greater your opportunities to monetize it.

Digitization

Digitization is the first D in Peter Diamandis’ 6D model of technological disruption leading to exponential growth. Digital data is easy to access, share, and distribute. It is the currency of the information economy, enabling digitization.

Platforms

Successful business platforms like Spotify, Airbnb, Uber, Netflix, and Amazon (SAUNA) drive massive value. They facilitate scaled interactions, exchanging units of value such as music, stays, rides, shows, and products. Enabled by the internet, platform businesses democratize access to digital data.

Language

The language of business is critical to success. It varies by sector, category, practice area, region, and specialization. For example, the language used in the US market for commerce to sell electric vehicles in the automotive sector. Making this language external for both humans and machines is a significant AI challenge.

Intelligence

The amount of and access to intelligence are increasing exponentially. Machine intelligence is rapidly surpassing human intelligence. Democratizing access to this intelligence across corporate and consumer landscapes opens limitless possibilities.

In Summary

Imagine an AI continent with 1 billion smart workers, paid in a few watts per day. They work tirelessly and only need instructions. These future digital workers are mobilizing today, marketed as copilots, agents, companions, and assistants. So, integrating them into blended teams or teams of teams is the next challenge.

As a teenager, I devoured ‘The Culture’ series by Iain M. Banks, which started in 1986. The series portrays ‘The Culture’ as a society that has moved beyond scarcity, where AIs play a crucial role in governance and societal structure. That’s right, many AI agents. Minds and Subminds possessing vast computational capabilities, personality and autonomy. Drones that service as assets, workers, and companions. And finally avatars that were physical extensions of other AIs us to interact with more directly with with biological beings. Banks was ahead of his time, exploring the co-existence of AI and humans.

AI Agents to AI Companions

The narrative of AI agents as human partners is still unfolding. Today AI agents are clunky, task-based, and largely confined to the realm of the tech-savvy. In the corporate world, AI agents, or co-pilots, are increasingly augmenting the digital workforce. Our AI agents summarize meetings, write blogs post, perform customer service, and make recommendations. But can they confidently unload your inbox. I don’t think so. That requires a higher level of sophistication, tact, planning, and intelligence.

However, in our domestic lives, we desire AI companions that help us accomplish more. And I prefer the term ‘companion’ over the corporate terms like ‘agents,’ ‘partners,’ and ‘co-pilots’. I want the trust of a companion with whom I can do things on a deeply personal and creative level. I wouldn’t share my companion, and my companion wouldn’t be suited to anyone else. My companion is an extension of myself. My AI companion could organize my wife’s 40th birthday party for me. However, my AI agent would make recommendations for venues with enough prompting. We aren’t there yet with AI companions, but that’s the goal.

So, add The Culture series to your reading list for a glimpse into the near future.

The Culture Series

1. Consider Phlebas (1987) – The first published novel of the series, set during the Idiran-Culture War.
2. The Player of Games (1988) – Follows a Culture citizen who is an expert game player that is recruited by the Culture.
3. Use of Weapons (1990) – Centers on an operative in the Special Circumstances division of the Culture.
4. The State of the Art (1991) – A collection of short stories and a novella, with the title story dealing directly with the Culture.
5. Excession (1996) – Involves the Culture’s encounter with an enigmatic and powerful artifact known as the Excession.
6. Inversions (1998) – A novel that can be read as a Culture book or as a standalone story, featuring two parallel stories that may involve Culture agents.
7. Look to Windward (2000) – Set in the aftermath of the Idiran-Culture War, focusing on the effects of the war on different individuals.
8. Matter (2008) – Explores the interactions of advanced and primitive societies within the Culture’s universe.
9. Surface Detail (2010) – Deals with the ethics of simulated realities and the afterlife.
10. The Hydrogen Sonata (2012) – The final novel published before Banks’ death, concerning a civilization preparing to Sublime, a concept frequently mentioned in the series.

The digital workforce is on the cusp of a revolution, an exhilarating fusion of human and artificial intelligence (AI) agents. This transformative wave promises to be nothing short of spectacular, yet it also poses a daunting challenge for those unprepared. I confess, the pace of change is staggering, particularly due to:

• The synergistic dynamism between Artificial Intelligence and Intelligent Automation (AiA).
• The rapid and widespread adoption of AiA by knowledge workers.
• The significant influence of AiA reshaping our digital workforce.

In a recent discourse with Lex Fridman, Sam Altman peeled away layers from the complexities of workforce transformation, diving into the realm of AI agents. Despite the turbulence surrounding OpenAI, Altman highlighted that GPT-5 would pioneer the widespread creation of AI agents, setting off a domino effect in the industry. What doors will this open for the digital workforce?

Flash Forward:

Picture a future where AI agents are integral to your team, taking on tasks and assigning them – not just to other AIs but to humans as well. With GPT-5’s advent, these agents are poised to undertake certain tasks autonomously, marking a significant leap in AI’s capacity to operate independently of human oversight. It will begin with essential, straightforward tasks and gradually expand to a broader functional spectrum, encompassing various interconnected modalities such as text, speech, vision, and video.

And what value will this add to knowledge workers today? In marketing, AI agents will manage data analysis, report creation, email sorting, programming, and even orchestrating marketing strategies, bestowing the invaluable gift of time. But what actions must we take – or avoid – to leverage this gift effectively?

Stop Overfocusing on Tech Innovations:

While staying updated is crucial, avoid becoming consumed by technological advances unless you’re in product development. The race for the latest model or parameter count is a distraction for consumers of AiA.

Start Dissecting Your Workday:

Deconstruct your activities into distinct tasks. AI agents will substitute tasks, not positions, but ignorance of your own workflows could leave you vulnerable to displacement.

Maintain Digital Workforce Expansion:

For organizations, continue the push for digital integration. This past decade has seen immense digital transformation – it’s time to literally digitize human roles. Understanding and documenting workflows are imperative, as is investing in AiA literacy for your workforce.

Though these suggestions may seem straightforward, their implementation is what distinguishes pioneers from stragglers in this AI-driven era.

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.

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 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

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 Trend	Minor Trend
Investment increasing	Confidence in right AiA investment bets
Likelihood of people replacement	Employee support for change
Workforce transformation	Expertise 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.

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.

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 

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.