When we talk about AI, the first capabilities that come to mind are that which were hitherto associated with the human mind – learning, reasoning, problem-solving, and the like. And while at its core, that’s what every AI solution is built to do, when looking at it from an enterprise’s perspective, AI encompasses operations like deriving business insights from large volumes of data, performing value-based tasks more efficiently, and extracting learning from large data sets without human involvement.
Although, several multinationals are reaping the benefits of AI by incorporating its capabilities within their business operations, many others are still in the early stages of AI adoption. This fact is stated by a February 2018 document published by IDC titled, “When Computing Becomes Human: Automation, Innovation, and the Rise of the All-Powerful Service Provider”,
which says that:
- About 1/3 rd of the global organizations are still in AI discovery/evaluation stages.
- Close to 1/5 th of the organizations are still planning to implement AI in the coming couple of years.
- Another almost 1/5 th of the organizations are running AI trials.
- And, only 1 in 25 organizations has deployed AI.
What those numbers blatantly point out is that when it comes to enterprise AI, several organizations are still very hesitant to take it on fully. But this article is meant to help them see that there’s no need to feel that way. AI implementation has its perks, if you use it right. And those perks are far greater than any other business strategy the organizations of the world have seen.
Why implementing AI is critical for enterprises?
There’s no dearth of online information when you look that question up, and every article will point you in the direction of these benefits that enterprise AI brings to the table:
- It helps automate and optimize tasks to save time and resources
- It increases productivity and operational efficiency
- It aids in faster decision making based on outputs derived from cognitive technologies
- It uses insights for making predictions with respect to customer preferences and behavior
- It helps mine vast amounts of data to generate quality leads and grow the customer base
- It helps increase revenue by identifying and maximizing sales opportunities
There are multiple businesses across the globe which are making use of AI in different ways to augment their capabilities.
Coca-cola uses AI to put the voluminous data it creates into perspective, mine it, and support new product development
IBM’s machine learning system, Watson, is achieving new feats in the field of art and design every day.
GE Power is using big data, IoT, and machine learning to build an “internet of energy” where these capabilities enable predictive maintenance and power.
American Express relies heavily on analytics and machine learning algorithms to sift through trillions of transactions and detect frauds in real time.
Similarly, leaders in the field of healthcare, manufacturing, retail, as well as media are making use of AI to boost their potential and gain and deliver more value.
In such a setting, an organization that’s still pondering over AI adoption might run the risk of getting started a little too late. So, in order to come at par with global businesses, it must start asking itself the right questions and take the single most important decision it can – is it ready for enterprise wide AI adoption?
Checklist to evaluate if your organization is ready to implement AI
If your organization deals with huge volumes of data regularly and your operations need to rely on data processing and analytics, you’re already facing the need for a sophisticated AI solution. So to evaluate how far you stand in the AI journey, try answering these questions:
- Are you capable of testing powerful AI frameworks optimized for the hardware upon which they’re running?
- Is your hardware optimized as an AI-ready enterprise data platform?
- Have you deployed modern data platforms like Hadoop and Spark that can help you organize unstructured data?
- Does your business have the required proficiencies and competencies to bring your planned AI applications to life?
If the answer to most of those questions is ‘Yes’, you know where you stand. Though there might be hurdles and bottlenecks along the way, you know you’re ready for the big change.
The journey to AI isn’t easy, but if you’re committed to your goals and have the right help, you can materialize your enterprise AI dream and be on the road for better returns. An AI platform can put you in a good position for advancements in AI use cases and other emerging technologies.