A lot is and will continue to be written on how to increase the adoption of GenAI technology in an organization. From my experience, the adoption of GenAI isn’t materially different from the adoption of any other digital technology, but the traditional challenges we face in technology adoption are absolutely exacerbated by the characteristics of GenAI.
Why is adopting GenAI so difficult?
The level of impact of GenAI adoption
Everyone is affected by GenAI, as its use cases are wide and varied. In traditional technology implementations, it may only be a department or function that is impacted, but with GenAI, it can be everyone, and the use cases will vary per persona group.
GenAI is constantly evolving
You cannot go a week/day/hour without a significant, new GenAI tool emerging from the marketplace. Some of these are an evolution of what has already been built, and some are a revolution to again subvert what we thought was possible. With this constant change, deciding what GenAI to build or buy, whether to implement now or wait for the perfect tool, is a real existential issue for many organizations. Then we get to the people side of things - how much change are your employees and customers prepared to absorb with new tools and process changes before frustration really kicks in?
Unclear expectations
Employees are particularly nervous about understanding the expectations of which GenAI tools they can and cannot use, how they should be using them and to what degree. This heightened level of uncertainty leads to fear, which can often lead to inertia - with your employees ignoring the challenge and choosing to deal with it at some uncertain point in the future.
A growing knowledge gap
Having the time and foundational level GenAI skills is a key requisite to learning and adopting these new sets of technologies, which some organizations have not properly addressed. We also know that many individuals do not prioritize GenAI learning amidst their multiple competing responsibilities.
In the face of some wide and complex challenges, and from our experience of helping multiple clients with GenAI, we are recommending eleven key drivers to increase GenAI adoption successfully.
Eleven key drivers to successfully increase GenAI adoption
1. Leadership direction and involvement
Your leaders must be aligned on the vision and direction of GenAI in your organization. Equip them with the right set of messages, spend time with them to ensure they really understand the change, and keep them updated regularly with key outcomes and success stories. You also need to ensure your leaders model the way throughout - get them to trial and adopt the tools early, embedding them into their working practices and using them with their teams.
2. Clear vision and messaging to showcase benefits
Getting your messaging right for a GenAI transformation is vital. Every organization will have a different angle to how they want to communicate this change, so it’s important you are aligned and consistent in this. Generally, your messaging goals will likely focus on areas such as;
- Inspire and leverage energy
- Replace fear with nervous excitement
- Highlight how GenAI adoption will improve their working lives, with specific success stories
- Show commitment throughout your organization
- Highlight how GenAI will unlock human potential
- Save time through productivity gains, utilizing this time saving to focus on higher value and impact areas
3. Address challenges sensitively and at the right level
While it is important to focus on and showcase the benefits of adopting GenAI, painting an entirely rosy picture can cause your employee base to lose trust in you and the change - feeling a little like propaganda. The five main challenges to GenAI adoption we have seen are:
- Job security - will my job be affected in the short, medium and long term?
- Ethics - is it right that I am using GenAI to do some of my role? It feels like I am cheating.
- Environmental impact - does GenAI have a detrimental effect on the environment, and how is the organization handling this?
- Risk - where is the information coming from, can I trust it, can I input information into this GenAI tool safely and what happens if I get this wrong?
- Spare time - what do I do with the spare time GenAI gives me through productivity gains? How is it assessed and reported? Who steers how this spare capacity will be spent?
It is extremely important to engage leadership and HR at the earliest stage to understand how they want to handle these challenge areas, both in their articulation and where if at all, any policies or guidance in relation to them is documented. You should also be clear and have alignment in how leadership should respond to these types of questions, should they be asked.
4. Focus on fewer high-impact areas, starting small and scaling up
There are a range of methods to deliver GenAI. We have found the most successful method is to choose a high-impact area for GenAI, rather than an area where you can make a small incremental productivity gain. With high impact comes high value, and a chance to showcase the positive potential of GenAI and the value adopting it brings.
5. Test, test and test again, using the feedback to iterate
Successful GenAI projects can often feature multiple rounds of testing, more than you would experience with a traditional digital transformation project. This could mean dozens of small A/B feature releases to an internal audience before you go live with your entire product to your customer base. Change management teams can leverage these multiple rounds of testing to gather deeper user insight, test different messaging and channels and better understand the persona impact.
6. Embed habitual GenAI usage into your workflows
Achieving the habitual usage of GenAI in your employee base is where you will really begin to see the value you are driving for being recognized. To make something habitual, you must ensure your GenAI tooling is embedded into your workflows, becoming a standard task or set of tasks to deliver the outcomes required. There are a range of methodologies and options to consider when building habits. These include but are not limited to, setting reminders, creating goals, making small changes first, monitoring progress and giving instantaneous rewards for small wins. Define these as part of your behavioral change approach.
7. Track value rigorously but pragmatically, intervening where required
The business value of GenAI, when considering the potential underlying financial and quality gains, is significant. From a change perspective, I would recommend creating rigorous KPIs to track success where you can, but I would caution against the dogged pursuit of KPIs to the point where you begin to see diminishing returns for your efforts. Where the baseline data exists, and you can track changes in GenAI adoption in a straightforward way, use these insights to target user groups with specific behavioral nudges to move them towards your value goals. These insights will come from areas such as ESAT, NPS, targeted surveys, focus groups/interviews, in-tool usage metrics, and in-tool feedback.
8. Build the underlying GenAI skills in your people:
Although GenAI tools have a variety of use cases throughout workflows, there are a number of foundational GenAI skills that organizations should be supporting their employees with learning. These include:
- Prompt engineering - how to create the right set of instructions for the GenAI tool so it gives you the best output.
- Scrutinize the output - GenAI is an amazing technological innovation, but it’s still in its infancy, and the results it gives you may not be valid. This invalid output is referred to as a ‘hallucination’.
- Bias mitigation - while your GenAI should be built to mitigate bias, it is a core skill for individuals to be able to recognize where bias may be playing through in the responses GenAI gives them.
9. Embed GenAI requirements into your HR and L&D key business processes:
The old adage of ‘what gets tracked gets managed’ is important when it comes to increasing GenAI adoption. Setting corporate, team and individual GenAI learning goals and threading these through your corporate goal-setting processes can be a really helpful way of highlighting the importance of upskilling in this area to your employees.
Hiring processes: When hiring new talent or hiring internally for new positions, set clear expectations about the GenAI skillset and mindset you are expecting of these individuals.
Career paths: Build in and set expectations on how GenAI will be a key component of career aspirations of individuals in your organization. Highlight what is expected of them at each level or in each role, and how you expect, even at a high level, individuals to be using and engaging with GenAI.
Performance cycles: As the world adapts to GenAI and its countless use cases, individuals need to be constantly challenging themselves to upskill and stay on (or towards) the cutting edge of GenAI. Having corporate, team and individual goals tied to measurable performance metrics will help ensure that the appropriate attention is paid to these areas as they are often tied to monetary rewards and promotion.
You must recognize that comprehensive and consistent company upskilling in the consistent use of GenAI is a significant time investment and cannot be completed in ‘magic time’. Organizations need to set aside capacity across teams and individuals to allow them the time they need to make this transition - that might be through mandatory training, team hackathons, brown-bag sessions or private directed study.
10. Foster a culture of innovation and experimentation with guidance and guardrails
GenAI will continue to evolve as it has from its more simple state of just plain old AI. New use cases will continue to emerge that GenAI can tackle, and so, of course, will the technology and skills that enable this.
Setting up a culture of innovation and openness is key to ensuring your organization stays on the front foot. However, psychological safety in individuals and teams is never a given when it comes to experimentation and innovation. Risk takers will tend to experiment more and be less concerned in general with whether it’s safe to add confidential company information into an exciting new GenAI tool. Those more safety-conscious individuals will not know what is safe and so may experiment much less.
I would, therefore, recommend some clear and consistent innovation and experimentation guardrails in these early years of GenAI. Market the tools you are actively encouraging and can be used freely, define those that can be used but not using company data, and which should be entirely banned from use. Keep this list simple, accessible, and up-to-date and give your rationale for the decision. This will support individuals in the future as they start to learn how to make more informed decisions on GenAI usage.
11. Measure and celebrate success, and share your failures
Proponents of GenAI are a vocal bunch… but the average person in your organization will likely bear some underlying (or overt) resistance to moving to a GenAI-enabled workforce. Winning these people over will take time, and evidence should come from sources they can trust.
It is important to measure a range of KPIs to get your people on board, such as customer satisfaction, employee satisfaction, NPS and system usage data. We’d also recommend sharing success and failure stories from a range of individuals who have either deep skill sets and/or high levels of social capital. Ask them to share their honest reflections and engage the wider audience in an open dialogue, as hearing from your peers can often be much more effective than a top-down, high-gloss leadership message.
Finally, look at how your early and high-usage GenAI champions can be recognized for their work and rewarded appropriately for supporting the GenAI transformation.
Conclusion
There are a range of change levers to consider to increase GenAI adoption, and the list above is by no means exhaustive!
Whether you’re just getting started with GenAI, experimenting with it or driving large-scale transformation, the role of change management is to successfully support your customers and employees working with the tools and delivering the value you are driving for.
Although GenAI transformations are very similar to traditional digital transformation projects, the speed is faster, the approach more intense, the knowledge gap deeper and the resistance to change much more varied. Engaging a change management team early in the process significantly improves your chances of success, working with them in partnership throughout.
If you're navigating the complexities of GenAI adoption in your organization, don't hesitate to get in touch with our expert team at Clarasys. We can help you craft and execute a strategy tailored to your unique needs, ensuring a smooth and effective GenAI transformation.
