This article was initially written as part of a PDF report sponsored by Iron Mountain and was written, edited, and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page. For better or worse, paper is often the lowest common denominator in capturing and storing this information in the enterprise. The inefficiencies of processing and distributing this mail to team members can challenge enterprise compliance, privacy, and information security requirements. COVID has strained enterprises further to drive towards digitization – but a vast array of important information is trapped on physical paper.

So maybe you can make it more tangible. But that's the understanding I have. Where do you really see digital twins driving value in terms of day-to-day decisions for executives who really need to steer the company?

One of the key factors in determining whether companies will thrive or fail in the next five years is how well they use the data they have available. This is a problem for many that may not even know what data they have, let alone how to use it or what insights it may contain. Business processes often involve creating or capturing data in a way that is siloed and difficult to access, analyze or act on outside of the process for which it was created. Even today, many business processes are reliant on physical record-keeping – note-taking, filling out paper forms, or ticking checkboxes on hard copy documents that are then filed away and forgotten about. Even if all a business's procedural documents and record-keeping is digital, the information is of little value unless careful thought is given to the data structure, format, and storage media that will be used.

NEW YORK – Everyone has seen warnings at the end of email saying, "Please consider the environment before printing." But for those who care about global warming, you might want to consider not writing so many emails in the first place. More and more, people rely on their electronic mailboxes as a life organizer. Old emails, photos and files from years past sit undisturbed, awaiting your search for a name, lost address, or maybe a photo of an old boyfriend. The problem is that all those messages require energy to preserve them.

Name Dropping is a Q&A series that aims to elevate the stories of women leading in the tech space. The idea came from Angela DeFranco, a Director of Product at HubSpot, who said one way to be better allies is to name drop more women in discussions of achievement, inspiration, and disruptors in tech, instead of referencing, time and again, the same set of (often male) leaders. This edition of Name Dropping features Fidelma Russo, CTO & EVP at Iron Mountain. What's the first thing you built that made you realize you love engineering? I'm an "accidental' engineer and went into the field because I loved math and science and didn't know what a different career option would be.

Many enterprises see the value in applying AI and machine learning to their business challenges, but not all have the necessary resources to do it. Where should your organization begin if you don't already have a team of data scientists, or if your team is fully committed to other tasks? Businesses need a quick and easy way to bring AI to their organizations. From the beginning, our goal has been to make AI accessible to as many businesses as possible. For example, last year we introduced Cloud AutoML to help businesses with limited ML expertise start building their own high-quality custom models.

Google Cloud announcements bring deep learning and big data analytics beyond data scientists, but enterprises will want more. If last week's Google Next 2018 event is any indication, Google Cloud is growing quickly. Registrations for the July 23-26 event topped 25,000, and actual attendance easily doubled the 10,000 at Google Next 2017. That's good, but if this public cloud is going to catch up with also-fast-growing rivals Amazon Web Services (AWS) and Microsoft Azure, Google is going to have to play to its strengths. From my perspective, Google's biggest appeals to big businesses are its deep learning (DL), machine learning (ML) and data platform capabilities (though I'm biased and my Constellation colleagues who follow G Suite and the rest of Google Cloud Platform (GCP) cloud infrastructure might see it otherwise).

Most enterprises already see the value of AI. In fact, more than 60 percent are in the process of adopting it right now. What we found, working with hundreds of enterprises, is that using AI comes down to simplicity and usefulness. Enterprises need tools that are simple and familiar, and they need to be able to directly apply them to their unique challenges. Today, we're making a number of updates to our data analytics and Cloud AI services aimed at making AI more simple and useful, and putting it in the hands of as many businesses and developers as we can.