Jan 29, 2024

Human-AI Synergy in the 2024 Workplace

In this article

As we enter 2024, the lack of a true seamless collaboration between humans and AI is blocking us from fully taking advantage of the potential benefits and impact of AI on the workplace.

In 2023, generative AI blasted onto the professional stage with the promise to redefine how we approach work. The potential for streamlining tasks, democratizing creativity, and elevating overall productivity is evident.

However, amidst these promises, a critical challenge that is inhibiting full adoption remains: Human-AI synergy is lacking.

That’s why in this article we will deep-dive into the concept of human-AI synergy. What it means, why it matters, and more importantly, the practical steps you can take to bridge the current divide.

Let’s get started with the basics.

What is human-AI synergy?

With human-AI synergy we mean:

A seamless collaboration between humans and artificial intelligence where each party leverages its strengths, resulting in heightened efficiency, improved output quality, and an overall boost in productivity.

Within this definition of human-AI synergy, the concept consists of three subcategories of synergy:

  • Synergy in interfacing
  • Synergy of context
  • Synergy of workflow

In order to achieve true synergy between humans and AI, all three subcategories need to be given the right amount of attention.

Let’s dive into each one and explore what we mean.

Synergy in interfacing

When we say synergy in interfacing, we mean synergy in the way humans and AI interact with one another.

Currently, interfacing happens predominantly via written input, in a chat interface. As a result, the speed of interfacing is limited to typing speed, which inhibits adoption. If you have to type an extensive prompt every time you interact with AI, in order to contextually enrich the AI and get an output that’s actually useful, it won’t take long for you to get back to doing things the way you’re used to.

Which brings us to the next type of synergy.

Synergy of context

The synergy of context revolves around establishing a shared knowledge foundation between human operators and AI systems. This ensures that humans and AI have the same information and data to base decisions on or to generate output from.

Bridging this gap in information access is critical for fostering collaboration between human intelligence and artificial intelligence. In the current reality, the context an AI has is what you give it in the prompt. In short: Synergy of context is lacking.

Synergy of workflow

The synergy of workflow revolves around the way AI is integrated into human-operated processes. Currently, AI sits isolated from a workflow until it gets called into action. Think about how you log in to ChatGPT whenever you need help with anything.

In a reality where synergy of workflow is optimal, an AI is embedded into your workflow, registers what is happening - potentially while handling routine tasks that you don’t want to do, and springs into action proactively whenever the need arises. It’s the holy grail of automation. Achieving this level of integration is crucial for enhancing overall workflow efficiency, and in the end speeding up the adoption of AI in the workplace.

These subcategories underscore the complexity of achieving true collaboration, as each dimension requires careful planning and thought when you’re working on the integration of AI.

In the following paragraphs, we will explore how to navigate and overcome these challenges to bring about full synergy between humans and AI in the workplace.

What does human-AI synergy look like?

Let’s start by stating that human-AI synergy is not something that can be achieved in one go. Not within the current reality of most companies, where the ways of working - from processes to software infrastructure - were not defined with the potential of AI in mind.

Successful adoption of artificial intelligence requires not only careful planning, but also a general understanding of AI advancements and the possibilities for synergy within each of the previously mentioned categories.

Let’s go through them one by one.

What synergy in interfacing looks like

As stated before, the current problem in interfacing is that the communication between humans and AI happens predominantly via chat, which is limited to typing speed. Furthermore, the most widely adopted AI systems are “open prompt” systems - meaning that you get a blank sheet on which you prompt and the AI generates output based on the information it has access to.

In the case of ChatGPT, that information is called the “Common Crawl”, a dataset which includes billions of web pages on billions and billions of topics. As a result, ChatGPT is a highly intelligent, but at the same time highly generic AI system.

Interfacing with a generic open prompt system in such a way that its answers are useful, requires extensive prompt building an, more often than not, a back and forth conversation until the output is good enough for you to use. Which takes a lot of time and leads to a user experience that’s far from ideal.

Thus, the first step towards synergy in interfacing is building an AI application that provides one-click-output that is useful instantly. This is achievable by designing user interfaces with built-in  dedicated buttons that do the behind-the-scenes prompting work for you.

For example, in a recruitment AI tool, recruiters can interview candidates and then interact with the meeting output - the interview recording - through predefined buttons that perform specific tasks: Summarize the interview, write a follow-up email, and so on.

This works best for repetitive tasks in your workflow.

If done correctly, you can get useful output from an AI tool in a matter of seconds. To keep the previous example, if you’re a recruiter and need to send a follow-up email to applicants after every interview, with proper synergy of interfacing, that could look a little something like this:

Which is already a great step in the right direction.

Now, if you want to take that one step further, you enter the domain of 0-click interaction. But more about that when we get to synergy of workflow. Let’s first dive deeper into synergy of context.

What synergy of context looks like

In a reality where synergy of context is optimal, the AI has access to the same data as you and uses it to generate contextually enriched output. Basically - output that is generated with the proper context around a topic in mind.

To make this concept a reality, organizations have to establish a centralized data repository - or get AI powered tooling with a similar functionality, then make sure the generative AI model has access to this repository, and let it generate output accordingly. In this setup, the repository serves as the source from which the AI system derives context, ensuring both humans and AI have access to identical data.

For example:

And this gives you drastically improved and contextually enriched output that has the potential to be directly usable without iteration.

What synergy of workflow looks like

Finally, the last step or prerequisite for true human-AI synergy is synergy of workflow. This might be the most important factor when integrating AI into your workforce.

Currently, AI sits on the sidelines of a workflow, waiting to be tapped and pulled into the process. As an entry level way of working with AI, this level or interaction is fine, but in the long run, it almost works against the true benefits of artificial intelligence systems.

If we’re moving towards a future where AI takes over all the tasks that a human should not waste time on, then this way of interacting will be a big detractor for future adoption and eventual synergy between humans and AI in the workplace.

In a reality where synergy of workflow is achieved, AI runs in the background of your processes, taking over the tasks it is designed to, and only reaches out to you when something out of the ordinary happens, or when your input is required. In this scenario, AI becomes a silent partner as opposed to a member of a tag team, and humans can focus on value-adding initiatives, while only looking at edge cases for the more repetitive tasks.

So now that we know what the ideal world of human-AI synergy looks like, let’s look at the way to get there. What should you pay attention to when implementing AI, to make sure that you achieve true collaboration between artificial intelligence and your workforce in the end?  

Steps to achieve synergy between AI and the workforce

In our pursuit of human-AI synergy, understanding the concept and subcategories is only the beginning. Translating these concepts into a workplace reality is where things become a bit more complex. As a result, a systematic approach for implementation is essential.

In the following section we outline a few high-level practical steps you can take to integrate AI into your ways of working, with synergy as the outcome.

1. Identify needs and potential

Obviously, before diving into the implementation of AI left and right, it’s imperative to run a comprehensive assessment of your needs and to have clearly defined goals. If you start with defining specific objectives, as well as tasks, processes, or areas where you think AI can contribute most effectively, it lays the groundwork for a targeted integration strategy.

When assessing these tasks and areas where you want to implement AI, the first question should be whether you require an AI-assisted, AI-executed, or AI-led solution.

  • AI-assisted means that AI only jumps in when called upon, or when necessary. For example, if you’re working on an idea and you want to explore different routes or angles, you can call on an AI virtual assistant to provide you with variations. In this case, AI serves as a brainstorm partner and assists you in the process of ideation, so the way of working is AI-assisted.
  • AI-executed means that the AI takes on tasks that you rather wouldn’t bother with. For example, writing a follow-up email with the notes and action items of a meeting to all meeting attendees. Something that takes up valuable brain energy and time, but can be perfectly handled by an AI as well. All that’s needed here is a final check of the human counterpart to make sure the message is solid, before sending it off. In this case the AI executes the task, but is not in the lead - hence, the AI-executed solution.
  • AI-led means that the AI runs a process autonomously, is in the lead in a few steps of a process and loops in a human when its part of the process is done. Think of the chatbots on many websites nowadays, that serve as a first line of interaction with customers who are in need of support. Artificial intelligence leads the initial interaction and connects the customer to an employee only when it deems the customer complaint unsolvable through standard processes. In this scenario, the way of working or the process is AI-led.

2. Decide if you need embedding or interacting

Next, you have to decide if the specific task you’re looking to solve asks for AI technology that’s embedded, or for an AI assitant you can interact with. The decision to embed AI seamlessly into processes or opt for interactive engagement depends on the nature of the task and the workflow you’re implementing AI in/for.

In principle, you should opt for:

  • Embedding, when you want AI to lead processes,
  • Interacting, when you want AI to assist with tasks,
  • If you need AI to help with execution, where and how the technology should be implemented will depend on the process.

3. Prepare to enable a soft landing

As with any type of digital transformation, successful AI integration involves preparing the people ‘on the ground’ for a soft landing. This includes providing adequate training for employees to adapt to the new AI-driven processes, and helping them understand what will change in their ways of working and why. The main goal here is to build trust and to remove unclarity.

Building trust and reassuring your employees is important especially if you’re looking to transform your processes by letting AI lead, or by delegating the execution of specific tasks to artificial intelligence. Some employees might fear that AI will take over their jobs, without seeing the opportunities it creates. It’s therefore crucial to focus on a talk track around AI augmentation and AI assisted work, where the human-AI collaboration takes centre stage.

4. Evaluate the impact of AI

After implementation, be sure to evaluate the results and the impact AI has on your workforce, processes, and outcomes. The “aha” moment can come quickly when working with AI, so be sure to evaluate its effectiveness continuously and seek out real-time feedback when you can.

In short: Talk to employees about their experiences with AI and make sure that they can share their thoughts via official channels. In the end, until true synergy is achieved, continuous evaluation is key to refining and optimizing the way you use AI in the workplace.

Regularly assessing the performance of AI integration against predefined objectives allows you to adapt, improve, and scale the scope of the implementation. This iterative process ensures that AI evolves in tandem with organizational needs.

Over to you

As organizations integrate AI into their workflows more and more, we envision a workplace where routine tasks are handled effortlessly by AI technology, decision-making is augmented by AI-driven insights and human expertise is augmented with AI capabilities.

It might sound like an almost utopian next step in workplace development, but we believe human-AI synergy will bring this reality to life, so we finally can optimize our ways of working and let human creativity truly flourish.

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