For businesses today, the disruptive and transformative capabilities of artificial intelligence (AI) are too great to overlook. The opportunity at hand to transform traditional organizations into dynamic, adaptive, and technology-driven enterprises has business leaders increasingly exploring ways to adapt AI and keep up with competing businesses.

Organizations that are unable to do so risk being left behind by newer businesses that are built on a digital foundation, unlike existing companies that have to undergo a digital transformation.

Many companies even struggle to achieve the short-term results from their AI deployments simply due to their approach to utilizing the technology. This leads businesses to assume that integrating AI with their processes is a lengthy and complicated process.

But in reality, it isn’t. In fact, one can indeed see instant results with AI deployments, and not just in one or two departments, but across the enterprise. This brings us to the question – How?

Besides installing AI tools and implementing the necessary and getting the right talent to operate and maintain these tools, businesses need to focus on three critical elements to ensure quick and large-scale results.

These three elements, namely analytical framework, context, and technology together form the A.C.T. strategy which ensures that enterprises not only integrate AI successfully with their processes but also leverage it to derive business value immediately following its deployment.

Let us look closely at the elements of the A.C.T strategy to see how they can help businesses achieve this.

Analytical framework

For AI to deliver its full range of problem-solving capabilities, it needs an efficient analytical framework to operate on. More importantly, an analytical framework is needed since businesses cannot simply put the AI on auto-pilot mode and trust it to produce real insights without understanding the business.

A framework, therefore, guides the process of building a custom AI solution which can be programmed to solve specific business problems. Furthermore, the framework can map out how and from where the data will be gathered for the AI to apply its predictive models and accurately forecast, say, for instance, the performance during a marketing campaign or when a particular customer will make his/her a purchase.

Context

The second factor driving the success of AI implementation in enterprises is business context, which enables an AI solution to perform in a manner and deliver results that help achieve larger business goals. Contrary to popular belief, AI is self-learning but not all-knowing and can only learn based on the inputs provided to it by humans or other connected systems.

For instance, AI will need all the customer budget information which the sales and marketing department has in order for it to make the right decisions on when to issue what offers, and which products customers find attractive at what price points. AI might continue recommending a past product simply because it has achieved more sales in the past or because customers have responded well to it.

However, the AI does not understand that new products typically generate more customer excitement than established products without the relevant context, which humans need to provide when building the solution.

Technology

Technology is the third and most crucial element of a successful AI deployment strategy, as it helps to put the various pieces together and ensure successful implementation of automated systems and processes. Comprehensive AI tools and solutions that can handle end-to-end enterprise processes are always a better option for businesses as compared solutions that are dedicated to very specific business functions.

Moreover, such solutions are not only more efficient in the long-term, but also eliminate the need for building a huge team to develop and deploy different solutions whenever the need arises. Furthermore, enterprise AI solutions and platforms are also easily scalable, allowing managers and leaders to tackle specific business problems across the enterprise and derive maximum value out of it for the entire organization.

When implemented with an A.C.T. strategy, AI’s real-world applications can deliver superior outcomes across all processes and departments, and create a seamless link between them. Businesses that are looking to adopt AI, then, can transform their operations and augment their efficiency by taking a multi-dimensional approach to enterprise automation with the A.C.T strategy. Consequently, this can be the key to gaining a lasting competitive edge in their respective sectors and markets.