As a sponsor and participant at Gartner IT Symposium/XPo™ 2024 in Orlando, the Grammarly team had the unique opportunity to witness what’s shaping industries and organizations worldwide. From foundational model releases to immersive workplace experiences, one thing is sure—the hype cycle and hypotheticals are long gone. AI is here, and chief information officers (CIOs) will be at the helm of how the technology matures across their organizations.
After speaking with hundreds of IT leaders throughout the week, it’s clear to me that enterprises are ready to move beyond the hype and get extremely practical about AI use. The phrase “What have you done for me lately?” comes to mind. That’s because, before they seriously consider any tool, leaders are now asking the following questions:
- How can we measure the success of the tool?
- Will the tool actually be used broadly?
- What ROI can I expect?
- Is the tool secure? (This is still the first question, but it’s one that has become more table stakes compared to capturing tangible outcomes.)
This is vastly different from a year ago when leaders were still getting a handle on whether to take AI seriously at all. In this year’s Gartner IT Symposium/XPo™, leaders were looking for frameworks and specifics, not pie-in-the-sky sales pitches.
After hearing from some of IT’s top thought leaders and executives at Gartner IT Symposium 2024, here are my seven top takes that will define the future of AI-driven organizations:
1. Two AI races and two AI paths
Like most disruptive trends in tech, it’s a race to the top. In the case of AI, though, there are two distinct races happening in tandem:
- Tech vendor race: The winning technology will build the best tool.
- AI outcomes race: The winning company will achieve transformative AI outcomes the fastest.
Most organizations are competing in the outcomes race and need to shift their focus to measuring and scaling AI ROI. And in the case of these races, there are multiple paths to take.
Companies today face a choice in AI adoption: the AI steady lane, implementing up to 10 initiatives for modest productivity gains, or the AI accelerated lane, racing to lead in AI-disrupted sectors. Both paths seek efficiency but come with distinct challenges. Companies on the steady track may lag due to limited use cases or productivity leakage, where gains don’t convert to meaningful work. Those on the accelerated track, however, face the complexity of managing multiple AI projects and ensuring consistent ROI.
Key takeaway: Understand which race your organization wants to run and choose your AI journey strategically, investing in frameworks that boost productivity and encourage the active and prolonged use of AI tools.
2. Unlocking value in unstructured data
The majority of enterprise data is unstructured, a fact that AI can transform from a challenge into an opportunity. According to Gartner, unstructured data represents an estimated 80% to 90% of all new enterprise data. Furthermore, it’s growing three times faster than structured data. Tools that can identify and use patterns in unstructured data (instead of strictly organizing it) make that unstructured data usable and have long-term potential. While the opportunity here is huge, so is the risk, especially when still-maturing technology like AI is given the keys to your most precious data. They say this is a lot like handing teenagers the keys to a Ferrari—there’s great power, but it also demands careful oversight and control.
Key takeaway: An AI trust, risk, and security management (or TRiSM, a term coined by Gartner) program in AI is essential. Companies must have policies to ensure ethical, secure, and transparent AI interactions, especially when they’re dealing with unstructured data.
3. Agentic AI and the new workplace
We’re entering a new phase in which AI goes beyond reminding us of tasks—it completes them. This evolution toward agentic AI, or AI that actively participates in meetings and even substitutes for users in routine interactions, marks a shift in how we work. Imagine an AI “dating profile” for each employee that prefilters decisions or tasks based on individual goals and priorities.
Challenge: As exciting as agentic AI sounds, there’s growing concern that reliance on it could erode critical thinking and situational awareness. To retain innovative decision-making capabilities, you must strike a balance between automation and human oversight.
4. Less is more, especially in customer experience
A compelling theme at the event was the need to simplify. Rather than adding endless features to enhance customer experience, companies like Google and Tesco are pioneering the “minus mindset.” They focus on eliminating unnecessary options, steps, and waiting times to streamline customer journeys. This “subtract to add” approach isn’t about just cutting costs but also truly understanding what customers need and don’t.
Practical application: Implementing “stop-doing” lists or regularly auditing customer-facing processes can be powerful. Simplified, streamlined interactions translate to a more satisfying experience and stronger customer loyalty.
5. Digital dexterity and the future-ready workforce
Investing in productivity-enhancing tools is only half the battle; employees must have the digital dexterity to use them effectively. Regular, daily use of AI tools correlates to higher productivity. But it’s a real chicken-and-egg situation: Do your employees who already know how to use AI use it more and are more productive? Or do employees learn how to use AI more productively as they use it more? The experts seem to think the latter. This skill isn’t just about knowing how to use AI tools but also about understanding when and why to use them. Looking forward, companies that focus on upskilling and building digital dexterity will have a competitive edge.
Key takeaway: Empower your employees to become builders, continually refining their digital skills and using AI tools to innovate. This is especially critical as middle-management roles are increasingly flattened, necessitating an adaptable, skilled, and engaged workforce.
6. Preparing for nonhuman customers
Yes, you read that right. Nonhuman economic actors are becoming a reality, with AI-driven bots capable of purchasing goods and services autonomously. These AI customers will change how businesses view marketing, sales, customer service, ethics, and trust.
What this means for us: As companies adapt to interact with AI-powered customers, robust ethical frameworks and security protocols will become essential. Companies must anticipate these nonhuman actors’ needs and interactions to serve both traditional clients and clients whose businesses originated and operate primarily online.
7. Guardrails for AI agents
As AI becomes more integrated and even indispensable, concerns about misuse grow. By 2028, it’s expected that 40% of CIOs will implement guardian agents—AI agents that monitor and contain other AI agents’ rogue actions. This approach ensures that AI agents act within specified parameters, especially as they take on increasingly sensitive tasks.
Call to action: Security will continue to evolve alongside AI, and proactive measures like guardian agents offer a layer of protection. Enterprises must prioritize AI oversight to mitigate risks from both internal misuse and external threats.
Final thoughts
While both buyers and guardian agents might sound like the plot of a futuristic fairy tale, there’s no denying we are on a one-way ticket ride to an AI society, whether we like it or not. Our focus at Grammarly is to ensure that enterprises have an AI tool that their employees love and IT can trust—and that allows leadership to draw a clear line between AI and ROI.
To learn more, you can read our latest announcement about enterprise features to boost productivity in the AI era, sign up for a live product tour, or contact sales to get a custom demo tailored to your organization’s unique needs.