Secure Intelligent Enterprise: Separating the Truth from the Buzz

Lou Flynn |  March 2020

Everyone’s rushing to create “smarter” versions of products we use every day. There’s intelligent healthcare, intelligent household appliances, and intelligent clouds. You name it, and most likely there’s a “smart” version.

Intelligence is expanding into every aspect of our lives, but it’s hard to determine what “intelligence” means in each scenario. This is especially true in enterprise settings, where things are already complicated.

We’ve seen that government policies, including The American AI Initiative, National AI R&D Strategic Plan: 2019 Update, and the DOD AI Strategy, are increasingly prioritizing components of the Intelligent Enterprise for investment.

It’s a good time to stop and look at what we really mean by building a Secure Intelligent Enterprise (SIE), and what that means for government agencies.

Defining a Secure Intelligent Enterprise

A Secure Intelligent Enterprise is not a product. It’s not a single project or initiative, or a cure-all for every agency legacy or data challenge. But wouldn’t that be nice?!

To break it down, a Secure Intelligent Enterprise is a company using modern cloud-based technologies, like Artificial Intelligence (AI) and the Internet of Things (IoT).

Companies use these technologies to better leverage data, protect their assets, and get desired outcomes faster – all with less risk.

It has to start with a commitment to modern strategies and processes powered by intelligent technology solutions. In this case, “intelligence” refers to applications that use machine learning and predictive analytics to power smarter decision-making and logic tools.

Agencies can use intelligent software-supported automation to offload repeatable and time-consuming tasks, achieving desired outcomes faster by automating processes around a unified data layer (or fabric). It’s an effective way to create more time for meaningful tasks.

What does this mean for the DOD, Intelligence, and other national security agencies? It means real-time insights about processes, threat environments, and adversaries.

It means more agile, responsive supply chains and operations that can meet the demands of accelerated tempos.

“In recent years, Artificial Intelligence and Machine Learning have moved from the status of ‘nice to have’ to ‘table stakes.’ Our adversaries are leveraging ML and AI, and we need to maintain our offset in the information domain.”Bob Palmer, MSIS, Data Science Cert.; Director of Software Solution Strategy at SAP NS2

 

If done correctly, Secure Intelligent Enterprises create a unifying data layer that uses AI-powered capabilities to integrate and analyze structured and unstructured data from multiple sources and formats.

If done incorrectly, you’re looking at failed objectives, increased complexity, and new vulnerabilities. Not good.

In reality, it can be challenging to scale data management and analytics and infuse apps with “intelligence.” It requires controlling data chaos in the cloud, on-premise, in lakes, and databases – not to mention systems on the edge processing sensor data.

The cloud is essential for creating connections across your data chaos – you can’t have an Intelligent Enterprise without it.

It doesn’t matter if you’re using an on-premise, public, or hybrid solution. That’s why the right partner is essential, and vendors are increasingly working together to meet customer demands. Experience and expertise matter when moving critical data and apps to the cloud.

How a Secure Intelligent Enterprise can help you

Once your agency understands how to implement a Secure Intelligent Enterprise, it can be a critical part of optimizing workflows. A Secure Intelligent Enterprise helps converge data from multiple systems to provide a cross-domain view.

Automated data discovery and integration mean agencies can spend less time on data wrangling, and more time analyzing.

Agencies can more effectively support mission goals, including planning and logistics, command and control, intelligence processing and exploitation, and data science and operations.

Real-time insights from across the entire data landscape offer a more complete, unifying operations picture, leading to more informed decisions.

Use advanced analytics with AI/Machine Learning to recognize unseen patterns, simulate outcomes, or use converged information to direct resources more efficiently.

Use improved intelligence analysis to help you outmaneuver enemies or competitors.

Again, Intelligent Enterprises are not a single fix-all solution or initiative. It’s a process of becoming more agile so you can move faster and smarter in the future. It may require several phases, a culture shift, and technology investments.

“Both the technologies and methods of Data Science have matured, and now leaders should move their organizations forward, beyond the ‘data science lab project’ stage towards delivering a robust ‘data science factory’ capability with enterprise standards.” – Bob Palmer, MSIS, Data Science Cert.; Director of Software Solution Strategy at SAP NS2

NS2 has the expertise and experience needed to help you on this journey.

We’ve got you covered with advanced data solutions to help manage the ever-growing data chaos, and the professional services and Innovation Labs to speed digital transformations. We can also work with your agency and any relevant hyperscale cloud providers to help you create a set-up to meet mission objectives.

Lou Flynn

Lou Flynn

Data Enthusiast and Manager, Product Marketing, SAP NS2

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