When designed and deployed strategically, generative AI tools can be accessible, highly secure and time-saving. And as a Solutions Engineer, I have a front-row seat to helping customers realize that optimal experience for their own business. I have seen how it allows organizations to ditch stifling processes and focus instead on value-added projects. Generative AI provides needed information within seconds and frees employees to do more impactful work.
Nudging an entire workforce toward a new process has never been easy, whether integrating generative AI into the flow of work or reminding Bob in marketing to stop ‘replying all’ to all-company emails. Change and adoption begin with recognizing the potential benefits of a process change and, in this case, a healthy curiosity for AI.
I regularly hear people voice concerns about enabling generative AI in the workplace. “My employees could never figure out how to use this”, “I don’t see how it would make a big enough impact” and “I don’t trust it” are common barriers I run into on a daily basis. It’s my job to alleviate those concerns and empower them to use the technology to their benefit.
Adoptability and Adaptability
Can this be adopted easily by everyone in my organization?
A companywide gen AI rollout will have the best chance at a successful implementation if everyone recognizes its value first. This recognition is becoming increasingly urgent at the executive level. According to Slack’s June 2024 Workforce Index, 96% of executives now feel a sense of urgency to integrate AI tools into their organization, with the portion looking to incorporate AI in the next 18 months rising sevenfold between September 2023 and March 2024.
Given this growing urgency, a great place to start is to lead with curiosity. Explain how the AI tool works on a surface level—don’t be too technical. Many generative AI solutions run behind the scenes or in the background. As a soft opening, consider having employees experience an AI tool on a trial basis. Give a no-stress message to the skeptics: Just try it! Once employees witness how AI can make their jobs easier, by eliminating mundane tasks or freeing up time for more stimulating work, they may use it more. After a short time, convene and survey employees. What were their challenges? How can this make their workload better or more streamlined? They may even spread that efficiency message to other departments or use cases.
Necessity
Do we really need this?
A major trend I’m seeing with adding generative AI to workplace tools is that companies just try to match pace with their competition, which can result in building or implementing AI products that don’t actually hone in on core user problems. To harness AI for meaningful efficiency gains, employees need to trust that this is a necessary improvement, not just another app to add to the ten they already use daily.
The ability to access and distill knowledge quickly exposes the difference between a company that effectively utilizes AI tools and one that doesn’t. I first experienced this when I used AI-powered search capabilities to gather technical information for a client during a call. Before AI, if a client asked me a question that I didn’t know the answer to, I would have told them that I would have to follow up with the answer at a later date. I’d then spend an hour or more searching through Slack or asking my peers for help. Now, I ask Slack AI the exact question my customer asked me, while on the call, and I’m able to get an answer to them right then and there. It may sound simple, but when you multiply the time-savings of getting a customer an answer in 5 minutes versus 3 days – you end up with faster deal cycles and project completions, more satisfied customers and extra time to focus on value-driven objectives.
Consider this: You’re on a tight deadline and need information from the engineering and marketing departments to complete a project. Generative AI dissolves those silos and makes accessing that information quick and simple. Imagine the time-savings when summarizing a long conversation between colleagues becomes a click of a button that gives you the bullet points from a month’s worth of work. There is no need to spend time digging when AI can do it for you. In fact, 81% of workers who have used AI for work say this technology is already improving their productivity. The top four work tasks where AI is providing the most value are writing assistance, summarization, automation of workflows, and research to learn about new topics. These capabilities directly address the time-consuming tasks that often slow down project completion.
Security
Is it secure?
In my role, I work with customers that have very high standards for data stewardship, and I regularly get questions about data privacy and security when using generative AI at work. Sure, AI can do awesome things and help you be more productive. But first and foremost, it needs to be a trusted and secure experience.
For example, when we were building Slack AI, we were very intentional with the principles that guided our data protection measures. Those included factors like ensuring customer data would not leave Slack’s trust boundary, not training large language models (LLMs) on customer data, and ensuring that the LLM only operates on data that the user can already access.
Before you implement generative AI at work, ask questions specific to the needs of your business in order to feel more secure about the safety and protection of your data. Those questions could include:
- How does the AI use my data?
- Is my data being used to train or fine tune LLMs?
- At any point, does my data leave its secure infrastructure?
- Does the AI uphold all of my existing security and compliance requirements?
Any company offering a gen AI solution should discuss these security considerations during onboarding. Share these findings with employees to help them feel confident.
A little skepticism is healthy and can help keep your data secure, but there are plenty of gen AI tools available now and in the works that are changing how we work.
