
The introduction of AI has changed the digital transformation goalposts. Referred to as “The Great Equalizer,” AI provides small enterprises with resources and features traditionally reserved for large ones, bundling new tech with the business agility that characterizes small enterprises.
AI transformation requires a new mindset and new skillset to best ensure success and long-term integration. The challenges should not be ignored, and focusing on feasible solutions can avoid future headaches. While it is impossible to predict the future of AI, anticipating frequent technology exploration as business as usual can make continuous transformation sustainable.
In the past days of digital transformation, progress could be slow, and changes were often done in phases, and with significant modernization efforts invested. Driving better business outcomes required significant time and resources. Now, AI has not only been delivering more contextualized results, but also made the path to achieve them shorter and easier to navigate. This has led to a new norm: A constant state of transformation. These major changes require leaders to adopt a new mindset and expectations, stretching the value and business outcomes of AI to meet their needs.
AI Offers an Equal, Time-Boxed Digital Edge for All…
Radical transformation was often out of reach for the smaller movers. Beyond the basics, setting up complex new systems to bring a business to the cutting edge was extremely costly. Major players had the resources to access the newest programs, while others had to wait. AI has turned this imbalance on its head.
It has come to be known as “The Great Equalizer” for a good reason: The costs of implementation are a menial fraction of what transformation required in yesteryear, and risk has plummeted. More than 80% of companies — both big and small — have already adopted AI in some capacity. Because of the relatively low risk and low cost, they have the freedom to test it out, play with the features, and discard it if they don’t like it with no significant consequences.
It is undeniable that AI will play a major role in the future of business — though it’s impossible to predict just what this role will look like — so refusing to adopt it has become unacceptable. It’s like setting up internet access or digitizing balance sheets back in the day: Adapt or be left behind. This proves to be true regardless of where the organization is positioned before the adoption of AI.
…And it Only Works Where Transformation is the Culture
Past digital transformation efforts have instilled an enduring fear of failure in the minds of IT technology execs. It is hard to forget the pressure of the time when the stakes were so high. The reality now is that experimentation with AI is encouraged from the very top. As there is no single AI solution, technique or technology that suits everyone, it is imperative to adopt a mindset of exploration and curiosity when dealing with AI rollout. Then, have the appetite to innovate, and keep pace with potential new AI technologies and approaches, the latter being the evolution from chatbots to agents. As long as the learning and improving process continues, “waste” or “failure” are usually time-boxed to early phases.
Leaders need to make sure everyone knows their roles and responsibilities and is on board the culture change. Successful AI initiatives in every case will look different for every organization, so agreement on what good looks like should be contextual and flexible.
Recognizing the Limitations and Areas of Risk
Do keep in mind that there is a time and place for experimentation. Creating premature dependency on AI before acceptance, transformation and socialization processes can lead to undesired results. The cautionary tales of AI mishaps, like Amazon’s sexist recruiting AI, are often due to a lack of preparation and rushed implementation. Wield the potential of AI wisely, letting innovation, acknowledgment of risks and experimentation work in tandem.
Experimentation is not a dodgy word, nor should it generate a lack of commitment. Instead, in the context of AI roll-out, it is designed to conduct AI infusion in the most effective way. It should create internal consensus on adoption and changes in ways of working (on personal, team or even enterprise level) that will be made possible with AI as part of the work routine. In this case, there is no such thing as too much communication or transparency.
Keeping a Vision in a Rapidly Changing World
The cliché is true: Change is the only constant when leading a sustainable approach to continuous transformation. Given levels of uncertainty, investment in skills to understand AI and adoption of ongoing transformation are lasting tools that will help organizations stay ahead of the laggers.