Google Cloud Next; from cost management to value creation

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The former range markers at RSPB Rainham

Google Cloud Next; from cost management to value creation

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Google's cloud business - encompassing everything from computing power to desktop productivity - has suffered an identity crisis throughout its life. For a company that generates an overwhelming amount of its revenue through services outside the cloud business (92% as of Q4 2021), the cloud side of its business seemed to have little direction other than the promise of cost reduction to prospective customers. With this week's global "Cloud Next" conferences, Google is signaling that it now sees the creation of value as the way to power its next growth phase.

Google’s cloud business – encompassing everything from computing power to desktop productivity – has suffered an identity crisis throughout its life. For a company that generates an overwhelming amount of its revenue through services outside the cloud business (92% as of Q4 2021), the cloud side of its business seemed to have little direction other than the promise of cost reduction to prospective customers. With this week’s global “Cloud Next” conferences, Google is signaling that it now sees the creation of value as the way to power its next growth phase.

Everything is AI nowadays

Amidst a raft of announcements across the entire range of the cloud business (Data, Open Infrastructure, Trusted and Collaboration), Alphabet CEO Sundar Pichai focused on Google’s role in developing its position in AI; to quote,” [Google has] always been an AI-first company.” The hero product to illustrate this – Translation Hub – was an interesting choice for several reasons. 

Firstly, Google Translation is very much a product that is human in scale. Sure, you can look at it transactionally and be wowed by the number of languages (185 if you’re counting) or processes per hour/day, and it’s impressive in that sense. However, as a business enablement technology, it fosters communication in a way that is instantly cognisant of value. 

Secondly was the inclusion of the “human in the loop” elements of Translation Hub. It can take an original, heavily formatted document and send it for auto-translation in a specified number of languages through that human loop for approval and then flow into language variants, preserving all the layout features of the original language master. It’sIt’s a workflow that will be very familiar to existing translation providers, where human power in the process is long established. However, this acknowledgment of the need for humans in the AI process felt significant for Google.

AI Agents for change

Pichai cited Translation Hub as one of the ranges of “AI Agents” that the company increasingly sees as necessary to increase the adoption of the heavy data science it’ sits already invested in creating at a platform level. Indeed in the release materials, Google states;

“”While investments in pure data science continue to be essential for many, widespread adoption of AI increasingly involves a category of applications and services that we call AI Agents. These technologies let customers apply the best of AI to common business challenges, with the limited technical expertise required by employees.”

It’sIt’s a statement that is hard to argue, and one of the early examples – Document AI – was covered by Deep Analysis earlier this year. Document AI received a couple of updates announced at Cloud Next Document; AI Workbench and AI Warehouse. AI Workbench is designed to create custom ML models more straightforwardly where the out-of-the-box models don’t provide the necessary accuracy on extraction. AI Warehouse is an amped-up search facility where you can search AI-extracted data and metadata.

In addition to the Translation Hub mentioned above and the additions to Document AI, the previously announced Contact Center AI now has the Contact Center AI Platform to extend capabilities beyond the out-of-the-box features of the previous offer.

Workplace

The collection of productivity apps, currently referred to as Workplace within the Productivity Cloud, has spent most of its life “”similar to Office but much cheaper.” ” Careers, if not fortunes, have been made in migrating workforces (and workloads) away from traditional desktop suites and toward Google’s Cloud. That momentum shifted a while back when Microsoft finally got serious about retooling Office. As such, Google’s external marketing message – and, critically, the sales techniques of their partners – had to evolve similarly.  

Grasping at the opportunity that the current shift to degrees of hybrid working provides the chance for Workspace to be the central meeting point that the Office once was. Ensuring that collaboration via video, voice, or through (co)creation of documents reflect that workforces could be meters or miles apart. Updates are – as ever – incremental and regular; automatic lighting/audio improvements and room attendee notices in Meet, speaker spotlighting when presenting Slides. The ability to create and manage custom document elements (“custom building blocks”), share variables, and use URIs (Uniform Resource Indicators) from internal and 3rd party applications (“Smart Chips””) is also clever and eminently usable.

As that “saving cents off the dollar by just being cloud” cost incentive has waned, Google has had to up the game with its productivity tools and now openly targets the employees to “no longer just replace but transform the way they work.” Workspace is used by 3 billion users worldwide, with Google suggesting that over 8m of those are now paying customers (disclosure: Deep Analysis is a paying customer of Google Workspace).

Scale is still impressive, but the value is not determined by weight.

Naturally, while there was a deliberate nod toward a shift from optimization for the cost to the creation of cloud-derived value, Google, like its peers, cannot help itself from discussing speeds and feeds. Central to the announcement of the new Vertex AI Vision product – for the analysis of real-time video and image streams – was the latest version of the Tensor chip (TPU), which, at least in part, enables it.

However, it was notable that Google explicitly suggested that it doesn’t care where data resides as long as it can stream to Google for processing and analysis. Hence, Google states that value will be where the decision is made rather than where the data resides. For example, Google announced the amalgamation of its Big Data tools under the Looker brand, with integrations to Tableau (Salesforce) and Power BI (Microsoft) to “look beyond the dashboard.” 

Perhaps as (albeit fewer of us), we pass through airports, the less we’ll see of 10x faster and 10x cheaper on every advertising board? It would at least represent a step forward if the boards boasted of the value created for employees or citizens.

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