What to consider as vendors add generative AI to workplace tools
Vendors of all shapes and sizes are rushing to implement generative AI, a race begun by the release of OpenAI's ChatGPT and its newest large language model GPT-4.
The newest tech vendor strategy is akin to a race for a participation trophy — if a vendor can give a tool or application generative AI capabilities, it will, from CRMs and ERPs to email, documents and presentations.
Microsoft unveiled a “new era of Teams”, featuring AI-powered filters for video conferencing, an AI-powered selling experience called Microsoft Viva Sales and AI-generated meeting recaps.
The Teams changes followed an earlier announcement teasing the integration of Copilot technology into Microsoft 365 apps, including Word, Excel, PowerPoint, Outlook and Teams. Google has followed suit, embedding new generative AI capabilities in its workplace tool suite, cloud services and search engine.
These high-profile vendors aren’t alone. Zoom is incorporating OpenAI’s technology to generate Zoom Team Chat and email responses based on input from existing chat, email, phone and meeting threads, the company announced. Cisco announced new AI capabilities for its Webex Contact Center and cloud platform, Webex Connect.
From end-to-end providers to pure-play specialists, technology companies vendors are racing to include AI in workplace tools, injecting intelligence into daily communication. In order for enterprises to get any value from these additions, business leaders have to put in the work.
AI-based tools have the potential to boost employee efficiency, productivity and creativity, but tech leaders need to communicate how employees can leverage tools so the technology benefits aren’t lost in the hype.
Prepping for updates
One area of preparation that IT teams need to think about is storage capacity, according to Bill Wong, principal research director at Info-Tech Research Group.
“Generative AI tools tend to be more memory and compute-intensive, [and] it is quite possible that with an environment that is more AI-enabled, employees may find that they generate more documents, presentations and analysis, which would increase the need for more storage,” Wong said in an email. “To prepare for this environment, the best practice is to build a data platform that is optimized for AI and advanced analytics.”
Cost is a huge barrier to entry for most enterprises when it comes to developing and implementing large language models internally. While accessing generative AI capabilities through vendors can be used as a workaround, tech leaders need to be mindful of smaller or niche vendors passing the costs onto customers, according to Wong.
Tech leaders are also worried about data privacy, a concern recently amplified after a bug in an open source library allowed some users to see other users' chat histories in ChatGPT.
Cyberhaven Labs research found there were more than 5,000 attempts in a single day to paste corporate data into ChatGPT per 100,000 employees.
“Since the large language models are in the cloud, all input is used as training data and available for any future query,” Wong said. “For this reason, several companies have totally restricted the use of technologies such as ChatGPT.”
Microsoft is placing parameters around its GPT-4 security offering to ease concerns, and does not plan to use customer data to enrich or train AI models in its Security Copilot, a tool announced recently.
ChatGPT bans at large enterprises and organizations have made headlines as companies try to limit risk and protect sensitive data. Nearly half of HR leaders said they are in the process of formulating guidance on employee’s use of OpenAI’s ChatGPT, according to Gartner data.
“Before training employees on how to maximize the use of generative AI, it would be useful to communicate the company’s policy on the use of generative AI technology, its responsible AI guiding principles and how it aligns with the organization’s mission and strategy,” Wong said.
Once policies are established, IT teams need to have the expertise and experience to assist workers throughout the enterprise as more generative AI capabilities are embedded into tools.
To maximize value, Adam Preset, VP analyst for digital workplace at Gartner, suggests companies should lean into the changing tech landscape.
“Get ahead of this wave,” Preset said in an email. “Understanding generative AI within common workplace tools should be a priority.”
Businesses can get a head start by getting involved with vendor beta testing previews, Preset said. IT teams that can use generative AI in daily work and develop skills will have a greater chance of adequately supporting other workers who will need help and best practices.
A large part of making generative AI tools useful is becoming good at creating prompts. If IT teams already have ample experience with this, it will be easier to pass that knowledge on during company training or one-on-one support sessions.
“The skill [that] workers will need to develop is prompting the generative AI so you can direct it to create a business proposal, an informal email, content for your website or something else fit to their goals,” Preset said. “It will be less about the beginning of filling in a blank page and more about clarifying what you would like as an outcome.”
“Then it’s about checking and double-checking that generative AI is giving you something trustworthy, true and useful,” Preset said.