Artificial Intelligence (AI) promises to make businesses more efficient and profitable, but they require an initial investment to be set in motion. As your company creates an AI implementation plan, here are some of the potential investment areas that you will need to anticipate.
How to plan and budget for an AI system
Artificial Intelligence (AI) systems for the enterprise are attracting billions of dollars in investments and predicted to make an economic impact measured in trillions. And no wonder: AI can empower companies to create new revenue streams (and bolster existing ones) while subsequently reducing overhead, thus opening the door to accelerated growth.
A study from Vanson Bourne found that 80% of enterprises already have some form of AI in production today. Similarly, a joint study by a HfS Research and IPsoft found a clear majority of IT decision-makers are developing (or have already developed) AI solutions for their businesses. The takeaway: if your company is not – at the very least – on the road toward implementing AI, then you are already behind.
While AI provides a path to future growth, it requires an initial investment in technology. Here are some of the initial costs you should expect as you move forward.
Build vs. Buy
Companies first need to decide if they are going to build their own proprietary AI system or work with a third-party vendor. Building an entirely new solution is bound to run into unforeseen hurdles which are difficult to anticipate budget-wise. Recruiting, hiring and keeping internal AI specialists is exceedingly difficult thanks to fierce, industry-wide competition for a limited supply of qualified engineers.
Customer expectations will change over time, as will the competitive landscape, and it is in your company’s interest to remain agile with the most up-to-date technology.
If your company decides to tap a third-party AI vendor, the first step is to consider the business goal that AI will be used to address, and then which vendor has the most optimal AI solution to meet that goal. For example, if your goal is to decrease customer service costs while enhancing the customer experience, a digital colleague with a proven track record of achieving those metrics, such as Amelia, should be on your investment radar. Amelia can become your company’s first contact with customers and provide them with 24/7 access to your systems. If you are looking for ways to streamline your internal processes inclusive of everything from network management to HR tasks to IT support, you should be focused on investing in a solution with autonomics and cognitive AI, such as our enterprise services platform 1Desk.
Companies should anticipate the time and costs of integrating AI technologies with legacy systems. While some stand-alone solution may technically fall under the umbrella of AI (e.g. simple chatbots designed to answer customer FAQs based on a static decision tree), AI that dynamically automates tasks across business areas (e.g. automating complex IMACD tasks across existing HR and IT inventory systems) will bring much higher value, as they have an ability to connect and integrate disparate systems. The real power of AI is in unifying business operations into a single platform.
Companies also need to consider where their AI “lives” and budget accordingly. Most solutions can be implemented on-premises or in the public cloud. The correct choice depends on the needs of your company and your customers. As a general rule, on-premises AI is inherently more secure, but AI that lives on a public cloud is typically cheaper to maintain.
Never stop improving
One of the great promises of software is that it can keep evolving and improving. However, this is also one of its great challenges, in that it requires a sustained investment in a dedicated team. Customer expectations will change over time, as will the competitive landscape, and it is in your company’s interest to remain agile with the most up-to-date technology. As AI makes your business more efficient, the savings can be reinvested in other innovative solutions (even additional AI) which can deliver additional returns to form a type of virtuous feedback