Employees are flocking to GenAI to boost their own creativity and automate mundane tasks. Yet despite early momentum, companies are grappling with how to parlay individual experimentation and value into a smarter and more productive playbook for AI-enabled productivity gains at the enterprise level.
Organizations are throttling investment in GenAI, lured by such benefits as increased innovation, improved products and services, and enhanced customer relationships. According to Deloitte’s State of Generative AI in the Enterprise Q3 report, two of three survey respondents confirmed increases in GenAI spending thanks to strong early value to date.
Even so, the majority of respondents (70%) have scaled fewer than 30% of initial GenAI experiments and pilots into enterprise production. Many are holding back due to concerns about risk management and governance. Less than one quarter (23%) rated their organizations as highly prepared for GenAI use cases at scale.
“Many workplace tools are embedding large language models (LLMs) and AI agents into their user experiences, but the key is for organizations to shift from experimentation to productivity improvements and business value quickly,” says Issac Sacolick (@nyike), president of StarCIO and author of Digital Trailblazer. “Organizations doing this well are focused on change management best practices.”
Upping the productivity game
So, what exactly are companies doing to raise the bar on GenAI productivity at enterprise scale? Foundry turned to the CIO Experts Network, a community of IT professionals and technology industry influencers, to gather insights for success.
There are a variety of tactics, some tried and true, and others more novel. But one thing is clear: From the get-go, it’s important to clearly communicate the business objectives of AI initiatives, set overall usage guidelines, and establish feedback mechanisms to drive continuous improvement. Early moves also include an analysis phase to determine what repetitive tasks can be discarded, reimagined, or automated, according to Arsalan Khan (@ArsalanAKhan), a speaker, advisor, and blogger.
To get users over the hump of ad hoc experimentation to embrace of GenAI to drive new work patterns, it’s important to demonstrate firsthand how the technology leads to working smarter, not harder. “GenAI can help analyze workflows, balance workloads, and spot risks like burnout, making work more productive and improving overall wellbeing,” says Gene de Libero, principal at marketing technology consultancy Digital Mindshare LLC.
Other recommended best practices include:
Highlight real-world examples. Encourage employees to think differently about how they work by playing out scenarios that speak to GenAI’s advantages. For example, every employee gets called into a meeting when they haven’t had time to properly prepare. Creating a demonstration that illustrates how GenAI could prep an agenda based on emails, summarize the week’s top challenges, and highlight everything in a crisp format that is meeting-ready in a matter of minutes goes a long way in convincing employees to change long-standing work patterns.
“AI acts like the assistant you never had,” explains Peter Nichol, data and analytics leader for North America at Nestlé Health Science. “Embracing GenAI might get you 90% or closer to being prepared for your meeting—now the five minutes before is spent tweaking nuances of the information, not generating it from scratch.”
Training, training, and more training. By providing comprehensive employee training on GenAI tools, employees are likely to stay current on the latest advancements and be better prepared to refine AI processes to optimize performance, says Robert Siciliano, CEO at Protect Now LLC. Training in the art of prompt design is a critical area of focus. Companies can create prompt design tutorials, encourage prompts tailored to specific roles, and create repositories that promote sharing of useful prompts with peers across the enterprise. Some companies have gone as far as to gamify prompt training with “promptathons,” and other contests designed to foster outside-of-the-box thinking.
Create GenAI safe spaces. Providing and promoting company-endorsed and supported platforms such as a secure GenAI “sandbox” environment is way to get users comfortable with new work patterns while minimizing potential risks like leaking sensitive and confidential materials. “Misuse of AI is often a result of low awareness of more secure alternatives,” says Chris Selland, partner at Tech CXO. “Making those alternatives available and raising awareness can go a long way toward enhancing productivity while reducing risk.”
Align with the right partners. Partnering with external experts like AI ethicists, researchers, and policymakers provides credibility to an enterprisewide GenAI initiative. It also ensures the organization remains knowledgeable and stays abreast of a fast-moving technology landscape.
Aspire for greatness, but double down on the basics. There’s no question GenAI is a transformational force for good and next-level innovation. Already, GenAI models are using sensors and drone footage to mimic animal sounds for research or melding culinary datasets with molecular gastronomy principles to unearth the next-best food sensation. While the possibilities are endless, a dogged focus on incremental improvements to basic work tasks holds the key to enterprise productivity gains. “Every day, 25% of employee productivity is wasted searching for emails and chatting on Microsoft Teams,” Nichol says. “An employee improving 1% a day is 38x more productive at year end.”
Evolve GenAI from assistant to proactive workflow orchestrator. Over time, GenAI can serve as a “decision accelerator,” a role in which it not only automates tasks, but also analyzes interdependencies and identifies bottlenecks across departments. “Productivity isn’t just about speed—it’s about removing friction,” says Shail Khiyara, CEO at Plutoshift AI and founder of the VOCAL Council.
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