On average, leading organizations will implement 10 AI projects this year to better enhance their operations, up from four just a year ago. A new Gartner survey of 600 companies reveals the four habits of the more successful ones.
The integration of AI (chatbots, etc.) will only increase as businesses look for ways to boost customer experience and automate tasks. A close look at the more successful deployments found four distinct habits among them. No single habit is entirely responsible for success or failure, but the pursuit of these four significantly increases your chances of delivering business value through AI.
Centralize AI oversight, but bring together people from across the organization
The Gartner survey showed that leveraging a variety of workers with different skills and diverse business insights–while still centralizing their strategies–helps lay the foundation for AI success. Organizations are more likely to be advanced in their AI capabilities when they build a task force to do so–one that is made up of AI researchers, data scientists, project managers, software developers, and more.
As one example, security professionals who might not be involved in an AI project but know about the technology and have used it for years can offer valuable reality checks and ideas.
Fifty-eight percent of successful organizations are using a balance of in-house and external hiring for their AI initiatives. Conversely, substantially more organizations that primarily hire externally are not yet successfully employing AI.
Formalize AI-performance accountability, decision-making, and budgeting processes
When top executives are responsible for the success of AI projects, and include AI resources in their budgets, the likelihood of success grows. More than three out of four organizations using AI today indicate that they have made specific C-level stakeholders accountable for how AI projects perform. Forty percent even assigned the AI budget to a corporate function, which displays the importance of prioritizing AI projects as an essential part of the business.
Limit your test projects to focus on the most promising opportunities
Although organizations are tempted to do as many AI projects as they can imagine, conducting too many experiments can actually hinder AI initiatives. Organizations employing AI have on average 4.1 pilots or proofs of concept (PoC). The survey found that the majority of unsuccessful forays were related to natural language processing.
Commit to financial and risk analyses of all AI efforts before and after implementation
Performing financial or risk analyses and practicing careful project selection is the last key habit that accompanies AI success. Half of organizations employing AI are running such analyses. Organizations best able to defend and promote their AI activities are carefully establishing a baseline to compare performance, determining key measurements to analyze effectiveness, and tracking them in detail through the AI project’s lifetime.
Enterprise leaders responsible for discovering the value that AI can bring to their organization should learn from these common activities and adopt them into ingrained organizational tactics.
Whit Andrews is a vice president and distinguished analyst in Gartner Research. Andrews focuses on organizational impacts, use cases, and business opportunities for AI. He also manages and maintains the Digital Workplace Survey, which examines digital workers’ attitudes toward technology, and establishes segments of worker type and style.
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