Artificial intelligence is the most electrifying and exciting technology in the business landscape. It has the potential to drive value across the business, particularly delivering enhanced customer experience, reducing cost and spurring revenue. From smarter products and services to better business decisions and optimized business processes, the technology can transform almost everything. However, before getting started with this disruptive technology businesses need to define their AI strategy effectively in order to boost revenue and accomplish business goals.

They must ask themselves how do they create a utilitarian AI strategy to harness its power? What exactly it brings for them and how it helps them in achieving their goals? So, to start modeling an AI strategy is very distinct from creating a traditional business strategy. An artificial intelligence strategy exists to support the business strategy.

Interpreting Your AI Strategy 

Turning to an AI strategy first requires defining strategy such as what is wrong and why. Guiding policies like ethics, foundation, culture and governance as well as coherent actions. Much consideration for the implementation process demands to determine whether an organization has a massive amount of data that exists or enough being generated. They will then need to ascertain which processes or teams are leveraging AI technology.

Most companies focus on positioning AI as a strategy to boost productivity to free up time and create opportunities for employees. But experts stress that before the understanding of AI that requires experimentation under uncertainty no one can start with AI strategy as a first step. And there is no one-size-fits-all for AI strategy to drive business efficiency. As for any AI strategy requires the core components including data, infrastructure, algorithms, which is surrounded by the pillars of skills and organization.

An AI strategy must be underpinned by a thorough, up-to-date data strategy. Without data, AI does not work. So, companies need to look at their data strategy too, in response to define their AI strategy.

Identifying the technology and infrastructure implications of the decisions businesses made so far can also help create an effective AI strategy. In this regard, organizations need to consider what technology is required to accomplish their AI priorities? Do they already have the right technology in place? And if not, so what technology they need to put in place that could seize the opportunity?

Moreover, developing a strategy for AI also requires in-house AI skills and capacity. In this way, businesses must look at where is the skill-gap and what they need to close those gaps? Do they need to hire new talent, train existing staff or work with an external AI provider?

Certainly, considering these strategies first would deliver an effective AI strategy for businesses that drive business success and revenue.

Though defining a strategy for AI not only have an impact on businesses or organizations level but also on a national or economic level. Most countries around the world in the last few years have established strategies and initiatives regarding artificial intelligence.

Countries like the United States, France, Australia, Canada, China, Ireland, Japan, Italy, Finland, India, and others have already come up with national AI strategy to encourage the use and development of AI and to address issues around it.

Undeniably, AI will have a generational impact as it is already driving massive shifts across the globe. According to PwC, AI could add US$15.7 trillion in global GDP by 2030.