This article was originally published on CIO.com.
Why not use artificial intelligence (AI) to step into your higher potential, automating a system that drives more dollar value out of your corporate IT investments?
Every business leader wants to be the next hero, praised for sharpening the corporate competitive edge. Business heroes are the ones who solve big problems by leveraging emerging technology to awaken new powers accelerating strategic outcomes. So, why not use artificial intelligence (AI) to step into your higher potential, automating a system that drives more dollar value out of your corporate IT investments?
It’s Time to Get More Value out of Accelerated Innovation
Thanks to years of accelerated innovation, businesses of all sizes are capitalizing on the agility of digital services and remote work. But at what cost? The challenge today is: How efficient and sustainable is your IT spending when it’s gone unrestrained over the past three years? Business heroes might even be taking on the task of curing a corporate digital transformational hangover. Consider that:
- While 78% of companies adopt the cloud, not all are seeing value of their investment.
- Cloud overspending can be as high as 70% according to Gartner.
- Roughly 29% of cloud investments go to waste, according to an upcoming CIO study.
- Shadow IT can consume 30-40% of IT budgets, and it’s not uncommon for companies to have 10-20 times more cloud applications than they anticipate—especially following panic-stricken video conferencing purchases.
Today, IT investments happen at warp speed, and afterward business leaders are expected to govern those investments, normalizing them into the company’s standards of operational excellence. That requires applying security protections to cloud investments and remote work, taking a recount of all IT resources after widespread changes, putting checks and balances in place to manage new assets, and realigning spending with business goals.
While anyone can achieve these goals, only those who can automate them will be celebrated as a hero. But as we all know, a hero can’t win the big prize without first going on a journey.
AI: the Journey to Intelligent IT Expense Optimization
AI is making hyper-automation the new business standard. In IT, machine learning and behavioral analytics are no longer used only for making sense of security threat data or predicting network service outages. They are now being applied to address the problems of IT cost control, vendor management, and financial administration burdens surrounding today’s highly distributed business ecosystems.
Much like a robot vacuum learns the layout of your house, AI-powered analytics can be used to study the entire IT environment alongside its associated services and expenses, correlating this information with usage data. Tracking cloud infrastructure, network connections, mobile devices, and their services generates granular data intelligence, allowing AI engines to “understand” current IT spending trends and “see” how effectively a company uses its existing investments. Let’s look at one example.
IT Service Sprawl: Championing Vendor Management with AI
AI is solving the problems of vendor management and provider sprawl—issues all too familiar to IT leaders handling an ever-expanding landscape of tools, services, and dashboards. In fact, it’s assisting with some of the downsides of software-defined networks (SD-WAN) and Secure Access Service Edge (SASE) investments when companies suddenly find themselves with an overabundance of internet service providers (ISPs) to manage. AI works to eliminate the manual work of handling hundreds of ISPs and other sprawling IT service providers.
How does it work? Advanced analytics observe network services, connectivity usage, and the costs of global links across multiple vendors, allowing IT leaders to make quick sense of highly complex telecommunications environments. With a mountain of data crunched across ISPs, voice, and all fixed wireline services, companies can gain contextual clarity into how they are using their network services all in one consolidated view for elevated insights.
AI-powered telecom expense optimization can:
- Eliminate the time-consuming need for administrators to collect, review, and correlate expansive datasets including inventories of services, providers, contracts, and service level agreements.
- Evaluate the usage activities of all network services in one dashboard, identifying unused assets, pinpointing billing inaccuracies, and streamlining the process of chasing down credits when network service providers fail to fulfill their SLA commitments.
- Prevent telecom service disruptions by automating complex invoice validation and approval processes to pay bills on time and accurately allocate IT costs across business units and departments.
This is one way AI automates IT expense optimization. Let’s explore the others.
Cloud Optimization: Awakening the Powers of AI and Closed-Loop Automation
Everyone is migrating to the cloud, and AI engines designed to automate cloud cost savings have two unique capabilities worth highlighting.
The first important distinction is AI’s ability to recommend solutions for the problems it recognizes. Big data insights and problem identification are the advantages of yesterday—actionable recommendations and automated problem solving are today’s biggest AI benefits. For example, AI can observe your corporate cloud infrastructure services and cloud application investments, essentially guiding you in how to use what you already own more efficiently.
An AI engine might recommend how to:
- Optimize cloud service provider contracts, using long-term discounts to lower costs.
- More efficiently use the cloud storage and servers you have in place.
- Get more savings out of pausing features, turning off services when they aren’t needed.
- Reduce redundant applications, consolidating providers to lower IT expenses .
- Pinpoint unused application licenses, helping reallocate resources to other users.
- Identify security risks associated with unsanctioned cloud applications.
The second important distinction: the ability for AI to automatically act on its own recommendations. This is the signature of advanced AI capabilities known as “closed-loop automation.” Not only can AI recognize the problem alongside the solution, but it can also make that solution a reality with just the click of an approval button. Tight integration makes this possible. Only when AI engines are connected to the cloud service delivery platform can they manipulate settings and make changes to the control panel on your behalf.
Closed-loop automation marks the moment when AI advances from a data intelligence service to a hyper-automated virtual assistant, doing the more meaningful work of actually solving the core problem.
Using the cloud cost optimization examples from above, here’s what closed-loop automation looks like in a real-world scenario:
- AI engine: Recommends using cloud infrastructure pausing features for the IT development environment because resources are only used during business hours.
- IT engineer: Clicks approve.
- AI engine: Uses API calls to implement changes inside your cloud service dashboard (inside the AWS environment).
This is the type of hyper-automation that gets business leaders crowned heroes. Automated problem solving is the true digital advantage because it literally accelerates business outcomes. Let’s face it, every business hero knows that nothing stops innovation in its tracks like the moment when a computer-automated workflow gets handed back to the human, essentially asking the employee to take it from there.
Arriving at Automated IT Expense Optimization
After accelerated innovation, harnessing information across the IT ecosystem is harder than it was just three years ago, and AI is the best tool for smarter resource allocation and tighter cost control.
The first step for business heroes is to apply advanced analytics to cloud and network services, so AI engines can start to understand what’s happening inside the IT environment. The key is to align AI to your strategic cost-savings initiatives, knowing which data streams coincide. After using AI to quickly recognize spending patterns and discrepancies between service usage and costs, it then becomes easier to advance into automated problem-solving using closed-loop automation.
Worried about How to Get Started?
Start with any functional area that is plagued by a combination of complex data with manual administrative processes and lean on IT expense management providers to usher in AI-powered platforms that simplify implementation through software and services. If you have a vast Iandscape of global IT services to cost optimize, look for a partner that can integrate with hundreds of IT service providers across the globe. The best expense optimization teams bring a library of IT spending insights, understanding the latest pricing information as well as how companies should shift their IT investments in response to economic pressures, remote work, and new technology trends.
In the end, business leaders crowned true heroes are the ones who save 15-40% of their IT costs by automating expense optimization. But in doing so, they also help their companies spend less money on the tools they need to simply run the business and more money on digital innovation.
Explore how Tangoe hyper-automates IT expense management for companies of all sizes.