A couple of years into the generative AI explosion is revealing the impact of these tools on employee productivity.
Here’s what you need to know from studies by:
- Nielsen Norman Group
- Boston Consulting Group
- Harvard
Here’s a breakdown of Nielsen Norman Group’s employee AI productivity research. You can download your copy here. These are my personal takeaways.
1️⃣ AI improves employee productivity by 66%
The 66% figure was calculated across 3 case studies the group worked with:
🤳 Customer service agents resolving customer inquiries in an enterprise software company.
✍️ Experienced business professionals (e.g., marketers, HR professionals) writing routine business documents (such as press releases) that take about half an hour to write
👩💻 Programmers coding a small software project that took about three hours to complete without AI assistance
The BIG takeaway: Users were much more efficient at performing their jobs with AI assistance than without AI tools.
Here are the results:
→ Study 1: Support agents who used AI could handle 13.8% more customer inquiries per hour.
→ Study 2: Business professionals who used AI could write 59% more business documents per hour.
→ Study 3: Programmers who used AI could code 126% more projects per week.
2️⃣ Narrowing the skills gap
This is one of the top things I’m most excited about with AI as a collaborative human tool.
The research found that generative AI narrowed the skills gap between the best and worst performers. That’s a huge win.
This is the business we’re in as L&D pros.
Supporting people to close their skills gap for performance and better career opportunities. Organisations don’t care about the latter but I feel a personal human responsibility on that.
We have an opportunity to reduce the skill gap with AI tools.
3️⃣ Learning at speed
The first study in this research provides an interesting revelation.
Customer support agents were followed for several months. The research found agents who used AI support achieved expertise faster than those agents without.
Here’s a direct quote from the research:
“An experienced agent can complete 2.5 inquiries per hour.
This level of productivity is normally reached in 8 months of work (without using the AI tool). In contrast, the agents who started using the AI tool right off the bat reached this level of performance in only two months.
In other words, AI used expedited learning (to this level of performance) by a factor of 4.”
Harvard & BCG: The impact of AI on work productivity and quality
This joint study by the smart minds at Harvard and Boston Consulting Group on ChatGPTs impact in work gives much food for thought.
Here’s what you need to know
The study at a glance
- Who Took Part: The study involved 758 consultants, representing about 7% of the individual contributor-level consultants at Boston Consulting Group.
- How It Worked: Participants were divided into three groups. One had no access to AI, the second had access to GPT-4 AI, and the third had access to GPT-4 AI along with a prompt engineering overview.
- What They Did: The study focused on 18 realistic consulting tasks to measure the capabilities of AI in a work setting.
The results
- More Tasks, Less Time: Consultants using AI completed 12.2% more tasks and did so 25.1% faster.
- Quality Over Quantity: The quality of work improved by over 40% when AI was involved.
- Know the Limits: Interestingly, for tasks that were outside the capabilities of AI, consultants performed 19% worse.
Insightful notes
Two patterns emerged for successful AI use:
- Type 1 Users: Some consultants used a mix of AI and their own skills.
- Type 2 Users: Others went all-in and relied heavily on AI for their tasks.
BCG AI at Work Report: 3️⃣ Key Takeaways
Here’s a breakdown of the BCG AI at work report. You can download a copy here. These are my personal takeaways.
1️⃣ Those who do vs those who don’t
Too often, we make comments on things we’ve never used or experienced.
That’s pretty stupid when you think about it.
Some stats that caught my eye:
- Regular users of generative AI are much more optimistic than nonusers (62% vs. 36%)
- Regular users of generative AI also recognise the technology’s transformative potential, both to improve and to threaten work
The data tells the story of a balanced view from those who use tools vs those who don’t.
The best way to be informed and make your own decisions is through experimentation.
Don’t be afraid to try your own experiments to form your opinions. Now is not the time to be left behind.
See page: 5
2️⃣ Leaders leverage AI tools more than employees
80% of leaders say that they use generative AI regularly compared to only 20% of frontline employees. That’s huge!
This piques my interest.
The report doesn’t provide enough depth into the data to show what influences this decision. We can take some guesses and make dubious speculations, of course.
A few that come to mind are:
- Leaders are more invested in owning their career development
- Better access to knowledge and resources
- Frontline employees worry more about their work being replaced vs leaders, thus, focusing less on upskilling
These are all assumptions.
Again, the message here for all of us is to take action and own your development. Explore the skills you’ll need to navigate the world of today and tomorrow.
See page: 8
3️⃣ People want to be upskilled
86% of survey respondents believe they need to be upskilled for AI.
Let that sink in.
On the other side, companies are trying to ban AI tools rather than educate their workforce on pivotal skills for the future. We can’t ignore this new technology. It’s happening whether we like it or not.
I shared an extensive plan for how you could do this in your organisation previously.
See page: 9
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