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It’s Time to Start Recording All Your Video Meetings

Are you recording your video meetings yet? All of them? You should. The future of your organization may depend on it.

That’s the conclusion I reached after noticing an AI-related announcement made by Cisco at the European edition of its Cisco Live end user conference earlier this month. The company unveiled its intention to launch a SaaS offering called Motific, which will be a cloud-based service that gives enterprise customers a centralized hub for managing generative AI – large language models (LLM), security controls, APIs and more.

Now, even as I write this, I already can envision all the puzzled looks that I’m triggering across the readership of NoJitter Nation. Certainly, most of us associate Cisco’s enterprise video initiatives with its Webex offering.- an application that seems far afield from Motific’s apparent focus in the realm of enterprise IT infrastructure. For many, the only thing that Motific developers would seem to have in common with the Cisco Webex video collaboration team is that Chuck Robbins signs their paychecks.

And yet – to me, at least – the Motific announcement is the clearest harbinger yet that the Age of Intelligent Video is at hand.

Over time, I fully believe that AI-infused technology solutions will transform video into the preeminent vehicle for capturing, storing and sharing corporate knowledge. But that can’t really happen until and unless enterprises get serious about implementing AI-enhanced solutions. Motific exemplifies the efforts of major technology vendors to attack the barriers that now slow the adoption of AI behind the corporate firewall. As AI becomes more widely used, enterprise video solutions will play a pivotal role in generating the data that powers a new generation of business software applications.

Building an “AI enterprise,” however, is no trivial task. In my anecdotal discussions with vendors and end users, it has become clear in recent months that security and other related concerns are prompting many organizations to take a “wait-and-see” approach when considering investments in AI-infused computing solutions. Indeed, these concerns over security may be the most common barrier to AI adoption for business applications.

The Motific announcement indicates that major vendors are aware of the skittishness of IT departments over implementing AI solutions behind the corporate firewall and are taking active steps to address those concerns in a way that will ultimately pave the way for broader adoption of AI solutions in the enterprise.

While we may not know the exact timeline for artificial intelligence to take root in the enterprise, Motific is a signal that vendors will eventually develop the security and implementation infrastructure necessary to make AI-infused applications commonplace on the corporate network. This opens the door to an entirely new breed of AI applications that will work with very specific, tailored datasets managed by organizations for in-house use.

This is very different from the types of “AI competition” storylines that have been unfolding during the past year or so. While billions of dollars are being invested by big-tech heavyweights and venture capitalists in the development of “large language model” platforms that aspire to be the front-door to all the world’s digital knowledge, history tells us that the titanic fight for dominance in the realm of “large language models” will not be the sole battleground of the AI age. We know this as fact because we’ve seen this movie before.

On a macro level, the rise of what we are now calling “artificial intelligence” is the most transformative change in the world of software development since the first flowering of the commercial Internet in the mid-1990s. In the nascent days of the web, vendors were tasked with creating solutions that capitalized on the realm of standards-based connected computing. Now, as we wade deeply into the AI era, vendors must develop productive ways to harness and leverage massive amounts of computing power.

In both instances, these are fundamental changes in the basic building blocks of technical innovation, offering a greenfield for software development with the promise of transforming retail, media, information distribution and a host of other application categories.

Indeed, a lot of the headlines from the early days of web development were generated by search engines seeking to establish themselves as “portals” to the Internet. Other big names made their way in e-commerce and online advertising initiatives.

But even as the likes of Google and Amazon were just cutting their teeth on the public web, another set of vendors – encompassing everybody from start-ups like Netscape to industry giants like Sun Microsystems – were trying to develop demand for an alternative use of web technologies for “Intranets.” The idea was to develop browser-based solutions for connected computing that could be implemented behind the corporate firewall.

As is the case with AI solutions today, many IT decision-makers back then initially were cool to the idea of using web-style applications on a corporate network. For them, security concerns outweighed the potential benefits and flexibility of this type of connected computing solution.

Of course, we don’t call them “Intranets” anymore. Browser-based solutions now are commonplace behind the firewall. That’s thanks – in no small part - to the vendors that chipped away at enterprise concerns over the course of time to win deployment of a range of web-style solutions that operate within the confines of the modern corporate network. Fast forward to today’s emerging AI era and the battle behind the firewall now shifts to developing applications and solutions that enable organizations to amass large datasets and implementing the applications that puts that data to productive use.

Cisco’s Motific is proof positive that the technology world still is willing to do the work needed to foster business adoption of a new generation of technical capabilities. Cisco simply is following the path once blazed by “Intranet” vendors, developing an approach for putting a red-hot emerging technology category behind the firewall.

Even with Cisco announcing work force cutbacks this past week, the company is pushing forward with projects like Motific. And, whether or not Cisco itself is successful with its Motific initiative, we can safely say that technology vendors’ desire to crack the code for enabling AI behind the firewall is alive and well. Once that code is cracked, enterprise-secure, AI-infused solutions will be a fact-of-life.

Once we accept the reality of enterprise AI, we can easily hopscotch our way to understand the growing importance of assembling corporate video meeting archives.

One article of faith for all AI solutions is that they create more value when working from large sets of relevant data. Indeed, one of the primary challenges for all generative AI companies has been in licensing and collecting inputs that can satisfy AI’s voracious appetite for data. Over time, we can expect companies building datasets for internal applications will face the same challenge.

So we must ask: Where is the data going to come from for training private enterprise AI solutions? These technology platforms can digest every e-mail employees write, every memo they share with colleagues and every PowerPoint they pull together for presentations. But what then?

Any student of human nature knows that most workers will have little interest in developing additional text-based content to train a company’s proprietary data archives. Rather, the best way to build datasets is to find ways to collect information on a passive basis.

Welcome to the wonderful world of archiving video meetings! Whether meeting participants are C-Level executives or entry-level associates, any discussions they take part in can generate information about an organization that could be useful in developing private corporate datasets over time. AI platforms will play a key role in extracting information that would otherwise be forever lost in unwatched video archives. Any input gleaned from meetings in this manner can – and should – be saved to make future enterprise AI applications more robust.

Certainly, one can expect that IT penny pinchers will balk at the costs of storing video meeting indefinitely. But if your business leverages any unique market knowledge or operational techniques, you really cannot afford not to do it.

The rise of AI brings with it a stark new reality: Competitive advantage ultimately will flow to the organizations with the best datasets. Robust data archives will be the raw material – in the form of digitized institutional knowledge – that powers the differentiated AI applications that streamline operations and boost productivity.

Allowing video meetings to go unrecorded today is the equivalent of letting all that corporate knowledge just disappear into the ether.