Be honest with me: Is your “digital transformation” stuck? Did you start in earnest a few years back, and now you’re sitting on half-finished projects, uneven outcomes, and a distracted staff? It happens. Maintaining momentum for multi-year efforts isn’t easy. Especially efforts that are increasingly broad and complex! We need a catalyst to focus our efforts, motivate our teams, and simplify our work. Early signals tell us that generative AI is that missing catalyst, and Google Cloud is a unique partner for your journey.

How you got stuck

Digital transformation means many things to many people. Is it about becoming more efficient? Upgrading tools? Delivering new digital products to customers? Adopting a data-driven strategy? Changing internal culture? All of those things? Google don’t always see a unifying purpose to these efforts that’s capable of rallying an organization. This lack of focus often results in a dizzying array of disparate projects. 

Some of these projects are focused on new customer experiences. You might have tried launching new mobile or web experiences with solid, but not spectacular, results. There are always a handful of backend projects initiated to adopt public cloud, establish a real-time data infrastructure, set up developer-friendly application platforms, and upgrade security services. This inevitably sparks modernization programs to make data more accessible, apps more scalable, and infrastructure more automated. Smart companies complement these technology efforts with promises to invest in a company culture that embraces modern thinking and elite capabilities.

None of those are bad things! But sometimes they come with unintended consequences:

  • More complex infrastructure that straddles public cloud and private cloud
  • Legacy systems straining under load and change rates that they weren’t designed for
  • Regularly changing measures of success, from innovation to cost savings to optimization to efficiencies
  • Team demotivation, as this growing bag of projects seems increasingly disconnected from measurable outcomes

There’s a better way. In our experience, a corporate investment in generative AI brings focus, meaning, and acceleration to a host of important IT efforts.

Why generative AI catalyzes your team

A business strategy with generative AI at the center benefits customers and employees. Why? For customers, it helps focus your attention on delivering more personalized and engaging experiences. There are at least 101 examples of that. For staff, it puts a spotlight on how everyone can use smarter tools to design, deliver, and operate products — whether those are data reports, software applications, or infrastructure platforms. Everyone gets to join in!

And that’s the thing. It’s not just about generative AI; it’s about what it takes to be good at generative AI. Everyone needs to come together to fully commit to excellence in five supporting areas (that were usually left half-finished during a classic digital transformation):

  1. Automate your infrastructure. Now’s the time to establish a full range of automation for provisioning, upgrading, and deleting all of the machinery that supports your (AI-hosting) infrastructure.
  2. Upgrade your data platform. Your AI models won’t be any good without good data. Timely, accurate data is critical, and that means investing in flexible data pipelines, scalable databases, and a data warehouse that’s ready for AI.
  3. Improve your developer experience. To build with AI, your developers need the tools, frameworks, and platform services that help them iterate quickly. It’s also time to finish those cultural upgrades that unleash your teams.
  4. Modernize your security practices. Embracing generative AI requires a whole set of data, application, and infrastructure security considerations. You won’t deploy it if you don’t trust it. It’s key to make the necessary upgrades to your security posture.
  5. Finish your cloud migration. It’s going to be hard to maximize the value of generative AI outside of the public cloud. Places like Google Cloud are purpose-built to support the access to innovation, elasticity, and scale that are so important right now.

What you need to succeed

Looking to avoid some of the challenges of past transformations? There’s more than one way to proceed with your generative AI strategy, but at Google Cloud, we see three crucial building blocks for your success.

You need proximity. Generative AI models and apps require proximity to dependent data. From AlloyDB to BigQuery, Google Cloud’s data services give you the speed, scale, and price performance to keep your AI-based systems grounded by your unique information. And especially now, you need proximity to expertise for your journey. This is a period of excitement and change, so you want Google’s world-class team partnering with you to help you architect, deliver, and optimize your AI-based solutions.

You need an integrated AI platform. This isn’t the time for building out complex, brittle, do-it-yourself AI platforms. Too much is evolving too quickly. Buy innovation and flexibility, not complexity. Our unique AI hypercomputerVertex AI platform for MLOps, and Gemini for Google Cloud offer best-in-class vertical and horizontal integrations that help you build, run, and optimize better than anywhere else.

Finally, you need cross-organization productivity assistance. AI is not just about different output; it’s about a different way of working. Gemini for Google Workspace helps everyone be more creative and productive. Gemini Code Assist gives software developers powerful tools for understanding and writing quality software. Gemini Cloud Assist will bring game-changing AI assistance to teams that need to troubleshoot and optimize their cloud systems.