Where Is Your Organization On The “AI Acceleration Journey”?

History has a way of repeating itself—but it’s always a little different each time. My first fully digital job was at The Chicago Tribune in the late 90s. Back then, the Tribune was a digital innovator—one of the few prominent publications to invest heavily in the Internet when broadband was mainly a luxury for the office, and AOL still represented the Web. I joined the Tribune as a Web designer for the publication’s Website and began my long and ongoing education in digital media and, more broadly, digital transformation. While Tribune Media had accelerated its digital efforts, many companies and organizations had no idea what they would do on the Web, and still, more scrambled to figure things out as Web adoption showed no signs of slowing down.

My second lesson in digital acceleration came when I led UX/Design efforts for one of my clients—WW Grainger, another organization that accelerated its e-commerce efforts and made significant investments in them. This investment paid off handsomely for the company, reflected in growing online sales, expansion, and company valuation. Of course, e-commerce is a staple for many businesses today and is at the core of their business models. Lastly, my nearly eleven years at global communications firm Edelman primarily focused on helping large organizations define and execute their strategies for dealing with a rapidly evolving Internet—first with social media, then turbocharged by mobile and broadband developments. In retrospect, so much happened in those eleven years that, looking back, it feels like a completely different landscape.

Today’s digital transformation imperative is a one, two combination punch:?

1. Data: More specifically, what organizations do with data to provide exceptional experiences to employees, customers, etc.?
2. AI: Bringing that data to life in incredible new ways that revolutionize business models, including disrupting new categories, uncovering ground-breaking efficiencies, and informing or accelerating new product/service offerings.?

The often-used adage about digital transformation is that it’s infinite—meaning it never ends, as technology constantly evolves. But there are moments of velocity and periods of acceleration similar to some of the previous moments I referenced earlier. When it comes to both data and Artificial Intelligence, we are at a critical acceleration point. This is why we put together this simple conversation starter for organizational leaders grappling with accelerating AI efforts across their business functions, geographies, workforce, and, if applicable, products. To that last point, organizations would be well served to look to the technology sector companies with no choice but to lean into AI acceleration. In addition to rebuilding its entire business strategy around AI, 微软 is actively hiring communications experts who understand the space in which to work with their executives as industry thought leaders. Meta , which recently launched ChatGPT like Meta AI, has standardized a watermark for their AI-generated images—any image created by a prompt fulfilled via Meta AI serves up a photo with the watermark: “Imagined With AI.” Meta is doing something that eventually all companies will have to contend with—signaling when artificial intelligence creates something of significance (in this case, an image) entirely generated by AI.

Beyond The Chief AI Officer

As with previous digital transformations—organizations are responding to the AI imperative by putting a chief leader or czar in place, but this only validates that we’re in the early stages of AI business maturity. We did the same with chief digital officers, who have largely become a thing of the past. Some of these AI leaders will help usher AI transformation across their organizations. Still, many will also fail—especially if they are put in place as more of a symbol as opposed to the beginning of a long and winding path where business fundamentals and AI technology advancements are reconciled. Appointing a Chief AI Officer is table stakes . Making an organizational business imperative to accelerate AI competencies across large organizations will take time, trial and error, education, experimentation, operational excellence, patience, diligence, and mastery of corporate culture to navigate if it is to impact the company's future significantly.

The AI Acceleration Journey: What Stage Is Your Organization At?

When working with client partners tasked with accelerating the company’s digital transformation, I’ve often found it helpful to have a preliminary conversation about the “stage” at which they think their organization is functioning. Thinking about assessing your company’s progress around AI in a big-picture, yet pragmatic way may not capture every nuance and data point, but that is the point—to simplify things so you can tackle the complexity over time.? This is far from rocket science, and in fact, it’s an often-used technique by executives and their teams to plot their course, update, assess, and reassess based on the changing dynamics. At a 30k foot level—the stages are defined as:

AI Aware

Being AI Aware means an organization follows AI developments, and the CEO regularly discusses its importance. Still, the organization itself hasn’t formalized initiatives significantly. A cohesive organizational vision and strategy have not been articulated. At the same time, informal learning and usage are happening at the individual employee level— initiatives going on that are decentralized at best. A data strategy that is foundational to AI acceleration is also fluid. In short, an AI Aware organization is doing many things around AI—but it is mainly experimental or hasn’t been operationalized at scale. This decentralized activity is one of the reasons organizations are looking to bring in a chief AI officer—to help put some formality to emerging AI activities.

AI Learning

An AI Learning organization takes the next step and prioritizes formalizing some decentralized activity so the broader organization can learn from it. Additionally, more “top-down” initiatives begin to take shape, establishing organizational governance and policy (it’s worth noting here that these efforts must be continually updated given the speed of AI advancements). This phase establishes a more thorough data strategy, operational considerations, and a roadmap. The organization has established clear and ongoing communications related to organizational AI Acceleration efforts. Along with a data strategy, it is at the AI Learning phase where IT/tech stack definition and evolution also become critical as the organization plans for updated tech infrastructure aligned with advancements in AI.

AI Experimenting

A key caveat of the AI Experimenting phase is the distinction that it is experimentation at the organizational level vs. at the individual level, so teams and leadership are involved, engaged, and driving the “experimentation.” At this point, the organization has been identified. It is in the process of deploying pilots to gather data points as it looks toward moving AI acceleration efforts to the end of scale and integration. The AI Experimenting phase also begins to formalize performance metrics. Sometimes, the metrics may be organizational learning; other times, they can be more similar to existing initiative KPIs. In any case, the organization has shifted from planning to planning, doing, and analyzing.?

AI Accelerating

Like any digital transformation, AI Acceleration doesn’t end—it begins a cycle where the organization is pushing forward while updating previous assumptions. All digital transformation is iterative by design. But in this stage, the organization is scaling, operationalizing, and adding roles and responsibilities to executives and teams where AI Acceleration is built into the remit. By this point, the organization has a clear strategic vision, the culture has been primed, and a roadmap is in place. Accountability becomes increasingly essential as the organization shifts from learning, experimenting, and showing proof points to making an organizational commitment to AI Acceleration supported by leadership from the top down and employee engagement from the bottom up. This stage is the beginning of the acceleration cycle—not the end.?

No Two Journeys Are The Same

AI Acceleration across the enterprise will be a different journey for each organization, and having an (honest) assessment of where the organization is currently functioning is critical. Generative AI is less than two years old, yet AI technologies such as machine and deep learning or natural language processing have been around much longer. Even the tech companies whose business models depend on AI are grappling with the changes Generative AI has wrought, as there is no doubt it is changing how we experience digital information. They are the canaries in the coal mine, but they are still learning and have a very different destination. For your next boardroom discussion—feel free to reference this framework and ask your fellow executives this question: Where do you think our company really is with our AI Acceleration efforts?

We’re working with organizational leaders in various stages of their unique AI Acceleration initiatives to help them navigate the journey. If you’d like to learn more about this, feel free to reach out.