Artificial intelligence (AI) is on the priority list of every leader who uses technology to grow their business. And today, every company is a technology company. Despite the hype around AI and investment in its capabilities, only around a third of companies say they have adopted leading AI operational practices, but a growing percentage are working towards it.
While AI is often seen as the golden ticket to bringing business operations into the 21st century – and it can – to do so, the technology must be approached specifically and strategically, not as a solution. all in one.
In the world of technology, one can imagine a solar system with interdependent capabilities. At its core, cloud technology serves as the sun – a central power source fueling and enabling other technologies. The underlying cloud platforms, such as Amazon Web Services or Google Cloud, provide the foundation for other capabilities to flourish in the technological universe.
Revolving around cloud platforms, there are various orbiting AI planets that rely on cloud infrastructure to provide solutions like automation, machine learning, robotic process automation, and more. Many business leaders are eager to enter the orbit of artificial intelligence solutions, but must first start by establishing the necessary foundations for successful AI implementations.
Once the center of the AI solar system is in place, to effectively unleash the power of AI, it is important for business leaders to understand what they are trying to solve. And while many vendors offer powerful offerings, AI is not unique in its approach or implementation. It takes multiple capabilities and applications to achieve true end-to-end AI results.
This ecosystem strategy can ultimately provide flexibility and stability to IT decision makers looking to leverage business data and drive meaningful results for their organizations. To demonstrate the importance of AI ecosystems, it is essential to discuss the current obstacles a company is trying to overcome and the specific AI capabilities that will solve for them.
The fake call of a one-stop-shop for AI
Today, business leaders are looking to define the function of AI in their organizations and how they can effectively implement AI given their current technology stacks.
For example, a banking executive may be looking to automate some of their company’s digital banking capabilities. To achieve this, the institution must consider how it currently houses its data, how that data will be processed and then refined for use, and finally how the data can provide insight to their staff and what information will be most valuable to them.
In this case, an organization may need to consider combining the technology and environment it has with new technologies and capabilities to achieve the desired result of a new automated banking tool. The lure of a one-stop-shop for AI needs can drive companies to invest heavily in a single vendor, which can create hurdles on the path to a meaningful AI-powered solution.
Part of the problem with seeing a vendor as a silver bullet is that companies can invest too heavily in a vendor that won’t help them move the needle on all of their specific AI goals. Given the high budgets that companies develop for their IT departments, it is essential to understand that investments are going towards the appropriate solution(s) and that more money for nebulous and all-encompassing “AI” does not always mean unlocking success. of the company.
Anthony Ciarlo and Frank Farrell, Deloitte
Additionally, the overall cloud environment in which an AI solution is deployed can make or break its success. This means that IT decision makers should have a clear understanding of their company’s solar system technology before implementing a new AI tool. When AI-related RFPs hit our desks, our first goal is to work on the specific needs of the client’s organization and whether the resources they put behind the AI solutions will get them where they want to go. want to be.
End-to-end, it’s difficult for a single vendor to meet all of an organization’s AI needs. Some are leaders in automation, while others are leaders in data analytics or machine learning. Understanding these different assets allows Deloitte to provide meaningful and personalized assessments of the investments to be made.
As a systems integrator, once the Deloitte team has a holistic view of an organization’s pain points, they can provide reliable recommendations on where to invest the money and how companies can get the best return on investment. in their technology budgets. The Deloitte team delivers the confidence to integrate and navigate the solar system to deliver the desired results its clients and their clients need.
The ecosystem approach to AI solutions marks a significant shift in how systems integrators should approach their customer solutions. In the coming years, it is likely that there will be increased collaboration between vendors in the market, resulting in more streamlined and transparent AI implementation processes.
The main driver of this change is continuing conversations with business and technology leaders who understand that AI is not an isolated entity, but rather serves as a key component in a solar system of platforms and of interconnected tools that can offer individualized solutions for the most urgent matters. challenges.
Anthony Ciarlo is Head of Strategic and Analytics Alliances and Frank Farrell is Director of Cloud Analytics and AI Ecosystems at Deloitte.