Novice to Native: A People-First Approach to Gearing Your Team Up for Generative AI
Are you excited about Generative AI and thinking about diving in with pilots and projects? Hold your horses and let's first consider how to get your team ready to navigate this brave new world.
In this week's edition of New World Navigator, we zero in on why a people-first approach to Generative AI (and AI more broadly) projects is absolutely non-negotiable and what you can do to adopt a people-first approach.
By “people first”, we mean prioritising the human element - understanding your team’s and organisation’s needs, addressing their fears and uncertainties, honing their skills, and nurturing their innate creativity - before diving deep into any of the technical implementation. Dive in as we unpack how to prepare and empower your team for the journey ahead.
The case for a people-first approach to Generative AI
When it comes to Generative AI, an increasing number of business leaders are today focused on the question of how to integrate the technology, and more broadly AI, into their operations, products, and services.
For most businesses however, this question is a premature one to ask. The level of understanding about Generative AI in most organisations today is nascent, laced with numerous uncertainties, and tends to be limited to a small group of technology champions and early adopters.
From a change perspective, Generative AI is particularly tricky. The potential breadth of its impact across all areas of business and society is unparalleled, which can leave many clueless as to where to start. The technology is evolving so rapidly that the latest developments today may be no more than a dim memory three months down the line. Therefore, rather than a top-down only approach that mandates exactly where and when the technology should be used, organisations are likely to find more opportunities with use cases and innovations that bubble up from the bottom.
Furthermore, few other technologies comes with as much “baggage”. These include ethical considerations around privacy and bias, through to fears that AI is on track to replace our jobs, and could even one day threaten humankind’s very existence. Introducing Generative AI into an organisation is therefore not at all comparable to bringing in a new ERP or CRM system. It’s introducing a whole new disruptive element with comprehensive impact that could completely redefine the working relationships that employees have with each other, their relationship with their leaders and managers, their relationship with the organisation, and even the relationship between your organisation and society at large.
In the context of most non technology-native organisations, there are therefore two critical prerequisites for integrating Generative AI into a business: a) ensuring that the team and broader workforce understand and is accepting of the technology, and b) that they have the required knowledge, practices, and tools to effectively, responsibly and safely use Generative AI.
All of this means that business leaders need to have a carefully considered people-first approach for bringing Generative AI into their organisations. Even more so than with other technologies and transformations, the role of leaders and management in shaping direction and narrative is critical, and not simply a “nice-to-have”.
In the rest of this article, I will share four key steps, including practical examples and tips, for getting you started on your people-first approach to adopting Generative AI.
#1: Addressing fears and uncertainties about Generative AI
Being people-first undoubtedly means that we should begin by addressing the fears and uncertainties about Generative AI. Every great technology in history, from the printing press to the Internet, was once viewed with trepidation. And with Generative AI, there are indeed some very legitimate fears and uncertainties. This is a complicated and messy area but no change programme can afford to ignore these concerns. Let’s consider some common fears and uncertainties.
Some common fears and uncertainties
a) The fear of job displacement is a real and common concern.
It's like watching Kodak and analogue cameras get displaced by digital cameras all over again, except in this scenario, you are Kodak. Yes, it’s undeniable that AI and Generative AI will end up replacing some jobs. But the same is clearly true of any technology. Before alarm clocks for instance, there were knocker uppers, who were kids that were hired to knock on windows to wake people up. Knocker uppers obviously disappeared when new job opportunities for alarm clock manufacturers emerged, but kids went on to earn their pocket money in many other ways.
By and large, Generative AI is augmentative. For many of us, it will be able to play the role of a diligent assistant, freeing us from mundane tasks and giving us more time to spend on higher-value work that needs a human touch (more on this below). Remember, AI can crunch numbers and write code, but it's still figuring out how to navigate a simple water cooler chat.
b) The fear of the unknown also looms large.
Let's face it: Generative AI can seem as complicated and mysterious as the plot of an avant-garde art film (but perhaps this says more about my inability to appreciate such films?). In fact, machine learning engineers and scientists remain largely unsure of how Large Language Models (LLMs) such as ChatGPT are able to arrive at their responses. The “black box” nature of many AI and Generative AI technologies is certainly not something that can be swept under the carpet.
What we can do however, is ensure that a) the outputs of the model are always quality-checked, and b) there is always a well-trained human in the loop. The latter’s role is to ensure the quality of the data going in, to make decisions on how outputs should be used, to make sure that Generative AI is not used for malicious purposes, or even to pull the plug on such technologies if they should ever become a threat to humans or the organisation.
c) And then there are the ethical concerns.
The ethical implications of Generative AI can make for a daunting challenge. Worries about privacy and misinformation, concerns about bias and fairness, attribution of and compensation for data used in training models, and the potential for malicious use (e.g., generation of illegal or harmful content) are just some of the many ethical quandaries that are emerging.
While Generative AI developers such as OpenAI and Google have made some strides over the last six months to improve the accuracy of their models, mitigate biases, and increase security against hacking attacks, a lot more remains to be done. Without a doubt, these ethical issues remain a significant and open risk for individuals and organisations alike.
How to address common fears and uncertainties
Leaders have a fine balancing game to play between painting an exciting vision of how they see AI and humans coexisting, and compassionately supporting employees through this change.
On the one hand, this involves creating positive energy and excitement by emphasising the benefits of Generative AI, chief among which is to get rid of tasks that are repetitive, dirty, dull, dangerous, or difficult (i.e., “the four D'"s”)!
On the other, it’s about openly acknowledging that there will be a period of change ahead - a potentially difficult one - where employees will need to upskill themselves to fully leverage AI, and which the organisation will be fully committed to supporting. There will be employees whose entire job scope, or large parts thereof, could be at risk, and it is imperative that they see their leaders acknowledging their most fundamental fear and anxiety head on and genuinely commit to supporting them in being upskilled. The goal should always be for AI to becomes an extension and expansion of human abilities, rather than a replacement of.
Should layoffs be unavoidable, then it is incumbent upon leaders to be compassionate and supportive. Sending an after-hours email - as a scale-up’s CEO recently did - to avoid confronting employees that is completely devoid of empathy or any gratitude to those being let go is definitely not the way to do this. Such tactics are in any case detrimental to the business in the long run as remaining employees and the wider job market are not likely to quickly forget such actions.
When it comes to facilitating this change, the most powerful thing a leader can do is address any fears and uncertainties head on. As a leader, make sure that multiple sides of an argument are given airtime, and allow for open dialogue and transparency. Prioritise putting in place strong governance policies (more on this later) and actively communicate measures that you are taking to ensure safety (e.g., ensuring a human is in the loop for all decisions). Above all, have empathy and patience for those who fear being left behind.
#2: Building AI / Generative AI literacy
We’ve talked about the importance of upskilling, and a big part of this is building AI / Generative AI literacy across the organisation.
What does it mean to be AI / Generative AI literate
This is not about training everyone to become machine learning engineers. It is about getting everyone in the team to a fundamental level of understanding of the building blocks of the technology, including its capabilities and limitations, and is crucial to promoting effective and safe usage of Generative AI.
I liken this to cooking a meal. You don’t need to be a gourmet chef with an intricate understanding of food chemistry to cook a meal. But knowing the basics of ingredients, techniques, and safety precautions will certainly make your kitchen endeavours more successful and enjoyable. The same goes for Generative AI – having a foundational understanding of the equipment (models), ingredients (data), techniques (algorithms, prompt crafting), and safety measures (guardrails) will go a long way toward helping you whip up amazing outputs.
Becoming AI-literate also helps with debunking myths and alleviating fears. It's like turning on the light to reveal there's no monster under the bed but rather just a collection of forgotten socks and an unfortunate potted plant. Getting to know Generative AI helps us see it for what it is: a tool. A fantastically efficient tool, a sometimes flawed tool, but a tool nonetheless.
How to build your team’s AI / Generative AI literacy
a) Curate and push free training courses
Progressive organisations are now starting to actively curate and push training courses out to employees. In fact, individuals and organisations should have little excuse when it comes to building AI / Generative AI literacy.
Free courses abound on the Internet. Some of the good non-technical ones include Google’s Generative AI training series, Microsoft and LinkedIn’s Career Essentials in Generative AI and Datacamp’s Introduction to ChatGPT. Please feel free to also access the recording of a webinar that I hosted in June on the basics and practical applications of ChatGPT and Generative AI.
Identify your pick of the litter and actively encourage your team to start learning. If you are a leader, then role model this - actively discuss Generative AI at team meetings, place it on the team’s agenda, and commit to advancing your own education.
b) Organise customised and more in-depth learning programmes
Some businesses may also benefit from more customised learning programmes that are designed to meet the specific needs of the team(s) and industry in question and developed with a sound understanding of the organisation.
While there are costs involved, tailored training courses such as the AI Fundamentals course that I run are likely to be more impactful, as these tend to allow for a more personal, interactive, and practical experience. These may also be suitable for organisations that are looking to adopt a “train-the-trainer” approach by upskilling small groups of internal Generative AI experts on a deeper knowledge base which in turn enables them bring their colleagues along the journey.
c) Encourage and enable continuous learning
Finally, because of the fast-paced nature of Generative AI’s development, it is important that employees and the organisation keep its knowledge fresh.
Some steps that leaders can take to foster a culture of continuous learning include providing ongoing training and educational opportunities, establishing mentorships and knowledge sharing forums, and maintaining an open culture that encourages experimentation and even productive failure (more on this below).
#3: Learning to work with Generative AI
Traditional tools perform specific tasks - hammers hit nails, saws cut wood. But what about Generative AI? It can help draft an email, develop a business case, analyse data, generate 3D models, and even compose a sonnet. The key lies in you and your team understanding that Generative AI is an open-ended system, capable of producing a wide variety of outputs. Of course, this expansive latitude it provides is both its strength and challenge.
Generative AI isn’t your traditional run-of-the-mill gadget
Unlocking this broad potential isn't as simple as typing a search query into a browser. It involves experimentation and creativity. To nudge Generative AI in the right direction, you need to provide it with appropriate 'prompts'. Prompting rarely works on the first try, and several tweaks may be needed before arriving at a response you are happy with.
Since Generative AI’s potential applications are so broad, it also helps if one is willing to try it in new and potentially unexpected ways. Some of my more creative use cases include using ChatGPT as a sparring and practice partner in advance of a negotiation, and asking it to adopt the role of a Devil’s Advocate to critique a presentation I had drafted. Yet these only happened because I was willing to attempt to test it in innovative ways.
Going further, Generative AI isn't your run-of-the-mill, 'plug and play' gadget, search engine or SaaS platform. In many ways it’s a bit of everything and more akin to a collaborator and partner. Microsoft’s soon-to-be released Microsoft 365 Copilot clearly tries to capture this essence: evoking the idea of a trusted wingman.
Learning to work with Generative AI therefore requires a shift in mindset. It's about nurturing an exploratory spirit, learning to phrase problems as solvable puzzles, and being open to AI's potential contributions. It involves developing a feel for AI, much like a chef getting a feel for spices or a musician for their instrument.
How to enable your team to learn to work with Generative AI
It’s very much about getting one’s hands dirty. Many users never get the hang of using Large Language Models (LLMs) such as ChatGPT and Google Bard simply because they give up after a few tries and see such tools as no more than glorified search engines. Take the time (and encourage others to do the same) to experiment and tinker with Generative AI tools. Like any good duet, it’s going to take some time to find your rhythm, but when you find your stride, you'll be able to create a symphony that's far greater than the sum of its parts.
Establish appropriate guardrails and governance policies (i.e., the Do’s and Don’ts) so that your team and workforce has the confidence to know that they are not breaking any rules if they try something out. Keeping mum about this topic tends to either discourage any activity at all or else lead to unchecked and potentially dangerous experimentation.
At the same time, facilitate safe bottom-up experimentation by providing employees with tools and resources. This could include preparing restricted “sandboxes” for employees to test our their ideas, funding (and rewarding) promising employee suggestions, etc. Ring-fencing a specific budget and a dedicated lead to shepherd such bottom-up efforts can also help ensure that the promising or advantageous initiatives receive the support and attention they deserve. For more in-depth discussion about this topic, read up on Adobe’s approach to inspiring innovation in their workforce.
#4: Becoming even more human
Thriving in the age of Generative AI requires two broad sets of capabilities. Firstly, the ability to partner with AI to get the best results (something we’ve discussed above). Secondly, it means leveraging our unique human strengths which machines cannot replicate.
Our uniquely human capabilities
Critical thinking and decision making, for instance, will remain prime currency in the AI era. A Generative AI model might spit out a novel solution, but humans ultimately need to be the judge and jury on its feasibility and ethical implications.
Then there's creative problem-solving. With AI taking over routine tasks, humans are freed up to tackle complex, creative challenges. AI can take on the role as your brainstorming partner, tossing around ideas, but you as the orchestrator and maestro will need to be the one who has to catch and shape them into something meaningful.
Communication skills (e.g., active listening, storytelling) also matter more than ever. Furthermore you have to be an effective communicator, not just with your colleagues, but also with your AI copilot. The art of prompt engineering - framing the problem for the AI in a way it can understand and which yields the most effective output - is all about effective communication.
Empathy, last but far from least, is a skill that AI is yet to master. Machines can’t differentiate between a human that is truly excited from one that is feigning the expression, and even if they could, they would need to be explicitly programmed to do so. You, on the other hand, can sense a colleague's mood, understand a customer's unstated needs, and respond with genuine empathy.
How to emphasise our human strengths
Societies will soon begin to even more disproportionately require and therefore reward those with the distinct emotional, interpersonal, and creative skills that no machines can ever mimic.
At the individual level, this will require us to reflect upon and strengthening our unique “human strengths” to sharpen our personal edge. Across organisations, it means investing significantly more in something that has traditionally been heavily underinvested in - soft skills training.
As an educator and trainer, soft skills courses (e.g., storytelling, influencing, and leadership skills) are by far my favourite ones to facilitate because they involve stronger human-to-human connections, and encompass more interactive activities such as roleplaying. When connecting post-course with participants, I find that the conversations inspired by such courses also go on to have a deep and lasting impact (e.g., more motivated and cohesive teams, better organisational alignment) for both participants and their wider organisations.
New technologies bring with them new opportunities and jobs. Generative AI is no different, and already new roles such as prompt engineers, prompt librarians, and Generative AI artists are coming onto the job market. These jobs play into the ability to work well with AI and are also likely to require the soft skills that we’ve discussed. Your organisation may not need these specific roles for some time to come, but keep a close look out for individuals and teams who have shown the ability and the willingness to lead the Generative AI charge. Consider how you might shape new roles (or hybrid roles) to enable them to continue exploring Generative AI alongside their other responsibilities.
Conclusion
The path ahead with Generative AI is an exciting yet challenging one. By taking a people-first approach - addressing fears and uncertainties, building AI literacy, learning how to work with AI, and leveraging our innate human strengths - we can ensure that humans continue to thrive alongside our new AI teammates. This strong foundation will be key to ensuring the sustainability and longevity of any organisational change and technology implementation being contemplated.
Justin Tan is passionate about supporting organisations and teams to navigate disruptive change and towards sustainable and robust growth. He founded Evolutio Consulting in 2021 to help senior leaders to upskill and accelerate adoption of AI within their organisation through AI literacy and proficiency training, and also works with his clients to design and build bespoke AI solutions that drive growth and productivity for their businesses. If you're pondering how to harness these technologies in your business, or simply fancy a chat about the latest developments in AI, why not reach out?