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Generative AI: Holding Promise for Transforming Employee Experience


Illustration of two heads exchanging ideas
Image: freshidea -

Seemingly overnight, with OpenAI’s December 2022 release of the ChatGPT chatbot, the promise of artificial intelligence (AI) has gone from niche to mainstream use. Any enterprise leaders who haven’t taken notice need to –– this will be a transformational technology for businesses.

As I explained in a research brief, ChatGPT is a large language model (LLM) trained on conversational text to generate human-like responses to any question imaginable in a matter of seconds and ask follow-up questions as needed. These answers can be long, like a detailed business proposal, or short, like an email. In releasing a free version of ChatGPT, OpenAI opened the doors for widespread experimentation using this powerful technology, known as generative AI.

LLMs are not the exclusive province of OpenAI, but the organization gets credit for bringing awareness to the masses. Earlier this month OpenAI released the fourth iteration of its general LLM, GPT-4, with the claim that internal evaluations have shown it to be “82% less likely to respond to requests for disallowed content and 40% more likely to produce factual responses than GPT-3.5.”

For enterprises, the real transformative power of generative AI comes when these models can be trained using internal business data. In theory, enabling employees to use generative AI in their workstreams will lead to big boosts in productivity while also positively impacting employee experience. This theory posits that generative AI will take away the drudge work, leaving them time to focus on more fulfilling creative or business-generating tasks, for example.

Examples are plentiful, for all sorts of employees: writing emails, creating marketing campaigns, turning spreadsheet data into presentation graphics, summarizing customer interactions, scheduling meetings among team members, creating employee surveys and capsulizing results in an executive report, and so on. When compiled using a company’s data, the content should be contextually relevant, or close to it. Critically important, at this stage at least, is human oversight. While the AI generates an email or marketing blurb, for example, an employee needs to review before accepting. What’s more, most tools not only require this, but also support iteration for style, tone, and even re-dos if the content isn’t quite right.

This is a here and now, with business application vendors large and small already having previewed or released products using generative AI, oftentimes powered by GPT exclusively or in combination with other LLMs.

Here's a look at how three business app vendors are approaching generative AI, as announced in recent weeks:

  • Google Workspace writing features – As a first pass with this technology, Google has announced a set of generative AI-powered writing features available for testing in Docs and Gmail. Calling this capability a “collaborative AI partner,” Google said employees will be able to enter a topic from which the generative AI will create a draft for iteration, including adjustments for tone and style.
  • Microsoft 365 Copilot and Business Chat Copilot is a generative AI capability for Microsoft’s widely used 365 business productivity apps, such as Excel, Outlook, PowerPoint, and Word, as well as its market-dominant team collaboration app, Teams. For Copilot, Microsoft combines GPT-4 and other LLMs with data in the Microsoft Graph and 365 apps to support contextual-based natural language queries of a company’s data. Embedded within apps, Copilot will enable employees to ask questions of it without needing to leave the app, thus maintaining a task workflow without too much interruption. Additionally, with its new Business Chat offering, Microsoft has enabled generative AI to work across all of a company’s business data and apps for knowledge sharing. Business Chat will be available within, Bing work accounts, and Teams. Microsoft hasn’t yet released availability or pricing/licensing information. (Note, this is but one of several generative AI-related product announcements Microsoft has made this year.)
  • Salesforce Einstein GPTAvailable today in closed pilot, this generative AI for the Salesforce customer relationship management (CRM) platform combines the company’s proprietary AI models with LLMs from partners, including OpenAI, and uses real-time customer data from the Salesforce Data Cloud. Customer-facing employees will be able to use natural-language prompts within the CRM to create AI-generated content for sales, service, marketing, commerce, and IT interactions.

Smaller app providers, too, are quickly venturing into generative AI, too. One example is Notion, which provides digital workspaces for knowledge sharing, project management, and collaboration similar to Google and its Workspace offering. In February, Notion released Notion AI, an integrated AI assistant that initially is intended to assist in authoring and improving content, creating document summaries, extracting key learnings from notes, and recommending next-best actions. Ultimately, Notion plans to expand its AI assistance to project management and its team knowledge base.

As these product examples show, generative AI is coming quick ... and it will change how employees interact with their apps and content. There are a lot of unknowns with generative AI, but business leaders can’t ignore the inevitability that it will end up in their workplace. Getting generative AI right will be an all-encompassing effort. IT leaders should provide perspective on security, compliance, and privacy, for example, while HR should lead on formulating policies around the use of and user training for generative AI. Take the time now to figure out how this technology could change how employees do their jobs, with an eye on productivity and employee experience improvements.