AI Assistants Improve Employee Productivity
Artificial intelligence is transforming businesses and workplaces around the world. As AI capabilities continue to advance, companies are finding new ways to leverage these technologies to boost employee productivity and efficiency. One emerging application uses internal AI assistants – conversational bots and other AI tools explicitly designed to help employees work smarter and get more done.
In a recent software spotlight podcast interview, Mike Heap, co-founder of My AskAI, discussed how internal AI assistants are being used to enhance productivity across various roles and industries. My AskAI provides customized AI assistants built on large language models like ChatGPT, allowing companies to train assistants using their data and content. Mike and his partner Alex Rainey founded the bootstrapped startup in December 2022 just outside London, England.
Streamlining Workflows with Automation
One of the most significant values of AI assistants is their ability to automate repetitive, manual workflows. As Heap explained, “AI can take on those mundane, repetitive tasks that humans don't want to spend their time on.”
For example, an AI assistant could handle scheduling meetings, organizing calendars, processing expense reports, filling out timesheets, and other administrative tasks. According to Heap, “Anything that's a repetitive, boring task is perfect for AI automation.”
By automating these repetitive workflows, AI assistants free up employees' time for more strategic, creative work that drives more excellent business value. A recent MIT and Stanford University study found that AI tools helped boost productivity for customer service agents by 14%, with even more significant gains for less experienced workers.
Improving Communication and Information Access
Another critical application of AI assistants is enhancing communication and access to information. Assistants can serve as always-available helpers for employees to get quick answers to common questions.
“Employees can ask questions in plain English, and the AI can go and find the relevant information from across all the company resources,” Heap said.
For example, an HR assistant could instantly answer questions about policies, benefits, time-off requests, and other HR-related topics. Similarly, an IT helpdesk assistant could provide 24/7 support for technical issues.
By providing quick access to information, AI assistants reduce downtime spent searching across knowledge bases and portals. They also ensure employees get consistent, up-to-date answers, improving quality and compliance.
Suggesting Tools and Connections
In addition to reactive support, AI assistants can take a proactive role in boosting productivity. As Heap noted, assistants can make data-driven suggestions to employees:
“The AI could say, ‘Hey, based on the work you're doing right now, here are some people you should reach out to, or here are some tools that could be useful for this project you're working on.'”
For example, the assistant could suggest relevant colleagues to connect with based on shared interests, skills, and experiences. It could also recommend helpful productivity tools, training resources, or internal job opportunities tailored to employees' goals and interests.
By providing personalized recommendations, AI assistants help employees find the best tools and connections to progress their work and careers.
Enhancing Creativity and Innovation
While AI excels at automating routine work, Heap emphasized it can also augment human creativity and innovation.
AI capabilities like text and image generation can help spark new ideas and accelerate brainstorming. As Heap suggested, employees can tell the assistant, “‘I'm trying to develop a new campaign around this product. Can you give me some ideas?' And the AI can provide creative jumping off points to build from.”
Combining AI's untiring idea generation with human judgment and creativity is vital. Together, they can ideate and iterate far faster than they could alone.
Challenges of Implementing Internal AI Assistants
While internal AI assistants offer immense potential, Heap acknowledged trust, transparency, and change management challenges.
Many employees are skeptical of AI's capabilities and wary it could take over their jobs. Companies must be transparent about how AI tools are used and clarify that the goal is to augment human employees, not replace them.
There also needs to be trust in what the system knows and how it operates. Heap said, “If people rely on an AI system to boost their productivity, the recommendations and information it provides need to be trustworthy.”
That comes down to training the AI responsibly with high-quality datasets related to the domain. Companies also need to audit outputs and continuously improve the assistant's skills.
Finally, change management remains critical even when trust and transparency are established. Heap advised rolling out AI gradually and getting employee feedback often. Companies can maximize adoption and realize AI's full productivity benefits with a thoughtful, employee-focused approach.
While internal AI assistants present challenges, companies deploying them already report tremendous productivity gains.
At one Fortune 500 company, customer service agents using AI software tools resolved tickets 14% faster on average, with a 35% productivity boost for less experienced agents. The AI provided conversational scripts that helped agents solve issues more efficiently.
Another organization reduced HR support tickets by over 30% by implementing an AI-powered HR helpdesk assistant. The assistant answered common questions instantly, saving HR staff time handling routine inquiries.
Across use cases from IT support to sales enablement, AI assistants prove their value in making employees more innovative and efficient. As Heap put it, “Where this technology is going to shine is taking away those repetitive tasks and allowing humans to focus on what they're good at – creative, strategic thinking.”
Implementing AI Assistants for Maximum Business Impact
For companies considering internal AI assistants, Heap provided several best practices:
Start small, learn fast
Run controlled pilots for specific use cases before scaling across the organization. Solicit employee feedback early and often.
Focus on augmenting people
Make it clear that AI aims to enhance employees' skills, not replace jobs. Emphasize it as a collaborator.
Use high-quality, relevant data that reflects your organization and culture. Audit outputs continuously.
Be transparent about capabilities, limitations, and use cases. Hold AI to high standards of accuracy and helpfulness.
Plan for change:
Get leadership buy-in at the highest levels. Invest in change management and employee adoption.
By following these guidelines, companies can implement AI assistants smoothly and see significant employee productivity, satisfaction, and innovation gains.
The Future of Work Powered by Internal AI
While conversational AI like ChatGPT grabs headlines, the applications for enterprise productivity are just getting started. Internal AI assistants are poised to transform how employees work fundamentally.
Repetitive administrative tasks will be increasingly automated, freeing human focus for high-value work. Answers and information will be instantly available at employees' fingertips. Suggestions and creative inspirations will flow directly from AI to employees.
With the right approach, AI can make every worker smarter, eliminating drudgery while amplifying human ingenuity and judgment. As Heap stated, “This technology, applied well, will boost productivity massively.” By deploying internal AI assistants strategically, companies can build more agile, empowered workforces ready to thrive in the age of artificial intelligence.
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Watch the My AskAI Software Spotlight podcast episode: Mike Heap and Alex built MyAskAI off previous AI products focused on fine-tuning GPT models. They created an easy-to-use platform for non-technical people to instantly upload content like documents and websites to create an AI chatbot. MyAskAI has seen significant traction, especially for customer support use cases, with the ability to quickly find answers in vast amounts of data and provide them to users.