How to leverage the artificial intelligence solar system
Artificial intelligence (AI) is on the priority list for every executive who uses technology to enable their business. And today, every business is a technology business. Despite the excitement around AI and investments in its capabilities, only about a third of companies say they’ve adopted leading operational practices for AI – but an increasing percentage are working toward that goal.
While AI is often seen as the golden ticket to take business operations into the 21st century – and it can – to do so, the technology must be approached specifically and strategically, not as an all-in-one solution.
In the universe of technology, one can picture a solar system of interdependent capabilities. At the core, cloud technology serves as the sun – a central power source fuelling and enabling other technologies. Underlying cloud platforms, such as Amazon Web Services or Google Cloud, provide the basis for other capabilities to flourish in the technology universe.
Rotating around cloud platforms, there are various AI planets in orbit that build off of cloud infrastructure to deliver solutions such as 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 building the necessary foundation for successful AI implementations.
Once the centre of the AI solar system is in place, to effectively unlock the power of AI, it’s important that business leaders understand what it is they are trying to solve. And while many suppliers have powerful offerings, AI is not one-size-fits-all in its approach or implementation. It takes several capabilities and applications to drive true end-to-end AI outcomes.
This ecosystem strategy can ultimately offer flexibility and stability for IT decision-makers looking to harness business data and drive meaningful results for their organisations. Key to demonstrating the importance of AI ecosystems is discussing current barriers a company is trying to overcome and what specific AI capabilities will solve for them.
The false appeal of a one-stop shop for AI
Today, business leaders are looking to define the function of artificial intelligence in their organisations and how they can effectively implement AI given their current technology stacks.
For example, a banking executive may look to automate some of their company’s digital banking capabilities. To get there, the institution must consider how they are currently housing their data, how that data will be processed and then refined for usage, and finally how the data can provide insight to their workforce and what insights will be most valuable to them.
In this case, an organisation may have to consider combining the technology and environment they have in place with new technology and capabilities to achieve their desired outcome of a new automated banking tool. The allure of a one-stop shop for AI needs may sway businesses to heavily invest in one provider, which can put up roadblocks on the journey to a meaningful, AI-powered solution.
Part of the trouble with seeing one supplier as a silver-bullet solution is that businesses may invest too heavily in a provider that won’t help them move the needle on all of their specific AI goals. Given the hefty budgets businesses are developing for their IT departments, it’s critical to understand that investments are going towards the appropriate solution(s) and that more money towards a nebulous, blanket “AI” may not always equate to unlocking business success.
“IT decision-makers must have a clear understanding of their company’s technology solar system before implementing a new AI tool” Anthony Ciarlo and Frank Farrell, Deloitte
Moreover, the overarching cloud environment in which an AI solution is deployed can make or break its success. This means IT decision-makers must have a clear understanding of their company’s technology solar system before implementing a new AI tool. When AI-related requests for proposal come across our desks, our first goal is to work through the specific needs of the client’s organisation and if the resources they are putting behind the AI solutions will get them where they want to be.
End to end, it is difficult for any one supplier to meet all of the AI needs of an organisation. Some are leaders in automation, while others are leaders in data analytics or machine learning – understanding these different strengths enables Deloitte to provide meaningful, tailored assessments as to what investments should be made.
As a systems integrator, once the Deloitte team has holistic insight into an organisation’s pain points, it can provide confident recommendations as to where money should be invested and how companies can see the greatest return on investment in their technology budgets. The Deloitte team delivers confidence in integrating and navigating the solar system to provide the desired outcomes its clients and their clients need.
The ecosystem approach to AI solutions marks an important shift for how systems integrators should be approaching their client solutions. In years to come, it’s likely that there will be increased collaboration across market providers, resulting in more streamlined, transparent AI implementation processes.
The key driver for this shift is continued conversations with business and technology leaders who understand that AI is not an isolated entity, but rather serves as a key component within a solar system of interconnected platforms and tools that can offer individualised solutions for the most pressing business challenges.
Anthony Ciarlo is strategy and analytics alliances leader and Frank Farrell is principal for cloud analytics and AI ecosystems at Deloitte.
