Operationalize AI and cloud at scale for differentiating speed

Stand apart from your competition by compressing time and cost – and build a customer experience that attracts and retains raving fans – fast

Imagine if you could reduce the time, it takes to adjudicate an insurance claim by half. Or onboard a new customer in a matter of moments, without interjecting a single human touch. Or speed a new product to market in a matter of weeks, versus eight-to-twelve months, leaving your competition to wonder, in awe, what just hit them.

A few years ago, when people were saying, “technology waits for no one,” the world had no idea just how fast “speed” would become the grand differentiator in business. In organizations, from banking and financial services, media and manufacturing, to insurance, retail and life sciences, digital technology is revising the landscape around the “haves” and “have nots.” The concept of an organizational operating system (OS) rich in artificial intelligence (AI) and machine learning (ML) capabilities is upon us, and for those who intend to remain in the game, adopting a modern AI: OS is no longer an option. It’s the way the game is played.

4 layers of AI: OS

To level set, AI: OS is an end-toend digital solution integrating four capabilities that most companies usually have dispersed across multiple providers: cloud engineering, domain and process expertise, AI and analytics, and execution. It can be broken down into four layers, as follows:

1. Execution: Last mile execution can be fully automated or have humans in the loop to complete the execution or to coach the AI models.

2. AI and analytics: This includes models located upstream to best automate decisions and processes.

3. Domain and process expertise: By encoding this previously unstructured information into a digital workflow, organizations can easily enable process redesigns by simply altering the underlying code.

4. Cloud engineering: Putting the Cloud at the core of the infrastructure introduces the capability to scale solutions.

By considering these four areas in the context of your organization, you can quickly gauge whether you might be a good candidate for an AI: OS upgrade.

It cannot be done without the cloud

Data stored in physical locations around the globe makes for an inherently slow operating environment. Waiting on multi-gigabyte files to be sent from one user to the next to resolve transactions is no way to achieve speed, especially in a world where petabyte databases have become the norm, and everyone seems to lack patience.

On the cloud, however, data can be accessed immediately from any permissible, browser-based device. Data storage becomes infinitely scalable. Metadata written into data files allows AI tools to scan massive data pools, identifying contextual associations and retrieving relevant information, on demand, in seconds.

As a result, elapse time for complex functions collapses, enabling near realtime responses and accelerating results in a competitive environment where every second counts.

Diminishing boundaries between technology, business and operations

Data is considered the crown jewel of many organizations, as it contains its history, identifies its customers and measures its ongoing success. Because of this, fears over data security are well founded. Poorly managed data can be exposed to the outside world and compromised. But in the last few years, new services and methodologies have emerged that offset those fears, making the cloud one of the safest places to store your data, as well as your operating infrastructure.

What’s more, as innovators across industries develop new AI, ML and automation technologies on the cloud, the cloud has become a treasure trove for tools and talent useful in streamlining operations and managing business. The fastest way to determine if an AI:OS is for you is by accessing these tools and talent and running a small pilot project with a cross-functional team of internal resources to establish its efficacy and share any knowledge gained.

Shifting into higher gear

While the benefits of accelerating business outcomes around a high performance AI:OS are enticing, there is always risk involved when changing the status quo. Industry experience proves that more than 70 percent of digital projects under-deliver. The reason why is that most digital projects tend to focus on automating a small piece of the business. Fragmented solutions do little to produce game-changing results. It requires a holistic view of the organization, its customers, processes, products, people and goals to move the needle. Incrementally, at first. Then, in greater leaps and bounds.

This is where an experienced, objective partner can lend great value. Look for someone with a broad industry track record in digital orchestration to help you reimagine the business. Someone who can help you quickly and effectively convert real-time information into clean data and enable it on the cloud. Someone with the change management skills to elevate your workforce for higher value tasks.

As you progress along the journey, monitor your elapse times in key areas of performance. Filing claims, onboarding customers, introducing new products. Anything that can dramatically help you reduce that time – by half, at least – will be an investment well made.

Take the discussion to the next level

To learn more about AI:OS and how you can employ it in your organization, click here.