Explore the five traits that AI pacesetters rely on to stay ahead of their competitors.
01
Promote A Culture Of Sustained Innovation
Culture fuels the AI race.
Setting the tone for AI adoption starts at the top and weaves throughout the organization. AI pacesetters benefit from strong executive leadership, a clear goal and a shared vision of success.
A culture of experimentation is a key trait of envelope-pushing AI enterprises, says ServiceNow Chief Analytics Officer Vijay Kotu. Such tinkering is vital to stay at the forefront.
Culture also helps leaders prioritize talent in the AI landscape. Too often, companies see AI’s capacity for automation to make processes only leaner and cleaner. But “you can’t shrink your way to success,” says Deloitte Consulting Chief Futurist Mike Bechtel. The right enterprise culture refocuses human capacity on the backlog of strategic work. “It’s why GenAI is rocket fuel, not a crash diet,” he says.
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say the C-suite is actively engaged with AI transformation.
02
Evolve Talent Development To Fuel Progress
Winning AI projects place a high value on the “people” component of the familiar people-process-technology framework.
Pacesetters are focused on cultivating the right AI skills across the organization through external hiring and internal training. Seventy-nine percent of AI pacesetters have programs in place to reskill employees and 61% organize AI learning events. The roles enterprises are most looking to fill are AI configurators, data scientists and experience developers.
As AI becomes more effective, executives will continue to value talent even if what we value in talent might shift. That’s because AI reimagines work and unleashes imagination. “AI is a catalyst for making us more human in our work,” Bechtel says. “With AI, people are going to matter more, not less.”
The net result? The people who practice empathy and possess creative problem-solving abilities will continue to find opportunities within organizations.
strongly agree they have the right mix of talent and skills to execute their strategy.
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03
Tie Investment And Measurement To AI Vision
Congrats on completing your latest AI deployment. But how will you know if your project will result in success or failure?
While an impressive 65% of respondents say their AI investments have yielded positive returns, only 35% strongly agree that their organizations have a defined set of metrics to assess that impact. Such a disconnect won’t do.
Knowing that you can’t improve what you can’t see, enterprises that lack well-defined key performance indicators to track returns on AI investments will struggle to get them funded. A robust framework of KPIs establishes the goals to evaluate against and can spur discussions on where to improve. “Being clear about metrics and investing in a continuous improvement management process is the best way to go,” Kotu says.
A willingness to deploy, measure and improve in a rinse-and-repeat cycle is what sets AI pacesetters apart.
sprint toward a defined set of qualifying metrics for measuring AI impact and ROI.
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04
Reshape How Work
Gets Done At Scale
Pacesetters are the front-runners in using AI to break down growth-impeding silos.
But if you count yourself among the others, then a practical first step is to audit operations to discern which processes would benefit most from AI.
“Lead with need and find the problem worth solving,” Bechtel advises. “Resist the temptation to focus on the shiny hammer. Instead, put your attention on the rusty nail.”
Organizations then need to route those imperfect workflows to an enterprisewide platform—with AI built in—that can automate the low-hanging fruit and streamline entire processes. Sixty-one percent of pacesetters have already deployed such a platform as opposed to 46% of others.
When used iteratively, AI can help develop and optimize new workflows on an ongoing basis. Pacesetters bet on these continuous improvement processes to pull ahead.
have established cross-functional workflows where collaboration between people and AI typically makes work more efficient.
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05
Formalize AI Governance
To Transform Ethically
Pacesetters understand that AI is a team sport.
In other words, technology and data governance need to play well together. Pacesetters formalize data governance policies to ensure transparency, ethics and fairness in AI project outcomes. They also train proprietary AI models in keeping with their long-term goals.
“The best way to manage AI models across the enterprise is to have a strong AI governance body,” Kotu says. These groups formalize governance and carry it out by evaluating risk in all its forms, including data breaches, privacy violations and intellectual property infringement.
While effective models can take different forms, basic rules of the game apply to all, says Dr. Rumman Chowdhury, data scientist and CEO of Humane Intelligence. These include: a clear representation of the values of the people it is impacting, an ability to change rules in a democratic fashion and an unwavering commitment to making sure AI puts people first.
are laying the groundwork for the AI race by making significant progress in formalized data governance.
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The good news for all enterprises is there’s plenty
of room at the top. The blueprint drafted by the
AI pacesetters is a good place to start. Using the
Now Platform from ServiceNow to strategically
unleash the power of AI can fast-track the process.
