If you’re reading this post in 2024, your organization is certainly talking about, or at least investigating, how generative AI will disrupt your workplace and company in the near future. Some organizations will be more cutting edge and ready to start today, while others are taking a more cautious wait-and-see approach – but nearly all will be evaluating workplace AI software either today, or in the coming months and years.
But what’s the right process to follow? What factors should organizations be considering, and what mistakes can they look to avoid making? It’s not all so straightforward. Many organizations are rightfully cautious about how they implement AI because they’re heard horror stories of implementations gone wrong, or have valid concerns about data security and the implementation processes.
Through implementing our workplace AI assistant with customers, we’ve witnessed plenty of missteps and challenges to workplace AI adoption. Today, we’ll tell you about the three most common mistakes that organizations make – and hope that in sharing these hard-fought lessons, you can take the steps to avoid these same mistakes.
The number one mistake that companies make? You guessed it – waiting too long to involve their partners in Legal and Security in the evaluation process. Too many companies in 2024 make it halfway (or more!) through their software evaluation or implementation process before finally looping in Legal and Security. When they’re involved that late in the process, Legal and Security can often risk derailing the entire initiative, or at minimum delaying the implementation timeline. And don’t blame them – they’re just doing their job.
So what do you do about this? Start by looping in Legal and Security early in the process, understand in advance their concerns and guardrails, and help steer the conversations on what standards your organization will apply to the use of AI internally and with the external vendors you bring on.
Some more details here:
Pro tip: Many Legal and Security teams will move faster to approve a “proof of concept” or “proof of value” pilot – compared to the heavy lift of thinking through an entire org-wide rollout upfront. We often recommend starting here, as it is a simpler evaluation process, and helps Legal and Security teams get comfortable with a vendor’s contacts and procurement process. Legal and Security’s core concerns around data and security will still need to be addressed, even in a pilot – but it’s often a more straightforward conversation compared to the complexity of discussing a full rollout. Plus, if you’re speaking to a best-in-class AI vendor, they should be able to answer your data security questions with ease. Make it simple for Legal and Security to approve your vendor, and everyone wins!
For a full list of things to consider when evaluating workplace AI solutions, check out our page on responsible AI.
Another common mistake that many companies make is having unrealistic expectations of what AI can actually accomplish in their organizations at this time. Executives see the latest Google Gemini demo or OpenAI demo, and think their organizations can replicate the same results by next week. The reality is that these demos are often showcased in squeaky clean lab environments, with perfect data – and wouldn’t stand up to how most organizations’ CRMs, emails, and data look. You know what we’re talking about, right?
So here are a few points to consider around managing expectations around workplace AI in 2024:
The final thing we often see organizations get wrong about integrating AI into the workplace is failing to devote enough time and energy to change management and adoption.
It will come as no surprise that not everyone in your organization may be as ready or excited to embrace AI as you are. There are a lot of valid concerns around AI and automation and there’s no point in minimizing employee feelings.
As a starting point, ask your employees which tasks they don’t enjoy doing. In an ideal world, what would they remove – or at least minimize – from their workday? What would they rather spend their time working on? If you can find AI assistants to automate part or all of the tasks they find cumbersome, this will increase employee productivity and satisfaction.
Companies also come up short when they assume there will be equal adoption across the entire organization. The needs of a marketing team are very different to those of a finance team. Not every department is going to be able to use assistants in the same way or to the same degree, and those championing the use of AI should be mindful of this.
We’ve found that organizations are more successful when they choose one department and run a pilot with it first. Ideally, the department should be one with a healthy amount of good data, complex processes, be metrics-driven and be willing to embrace new tools.
The results of the pilot will help your organization make any necessary changes and drive company-wide adoption down the road. Remember – you don’t have to roll out AI across the organization all at once. This will often bog you down in evaluation purgatory. Just start with a pilot with one department. By breaking things down and learning as you go, you’re setting your company and employees up for long-term, lasting success.
Adding in a workplace AI tool means you’ll have to reshape internal processes and procedures. Here are 3 steps to doing this effectively:
At Ask-AI, we found ourselves overwhelmed by product-related Slack messages that only a handful of our team could answer. Not only was it time-consuming, but it led to delayed responses to customers and opportunities. We tried creating and directing the use of “ask-product” or “ask-support” channels for a while, but these channels got overwhelmed soon enough too – this was a band aid solution at best.
So, we pivoted and came up with a thoughtful way to use our universal AI assistant.
Here’s how we did it:
After integrating the Ask-AI assistant, we developed a new process for all employees when it came to asking product or customer -related questions:
While it was challenging to break the habit of using Slack, eventually everyone caught on. The more we used the AI assistant, the more it improved. Successfully implementing and shifting this internal process resulted in a 30% drop in Slack questions and an 85% drop in repeated queries.
We all know that AI is here to stay and is already changing the future of the workplace considerably. The organizations that will emerge as winners are the ones who will take the time to thoughtfully plan their workplace AI strategies before pressing ‘go’ and then continually refine their approach as new information comes to light. Hopefully this article helps you avoid the three most common pitfalls we see organizations make – and sets you up for success in your AI adoption journey.
Interested in learning more about how Ask AI can help your organization save time? Let’s talk.
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