AI continues to transform industries across the globe, and business decision makers of all kinds are taking notice. But there’s a problem: although 80% of today’s enterprises recognize that AI is critical to their future, only 14% succeed in harnessing it (source). In other words, a gap remains between the potential of AI and its ease of deployment.
At Google Cloud AI, closing this gap is perhaps my most important responsibility. After years of breakthroughs, AI has stabilized with the emergence of sophisticated tools, best practices, and a rapidly growing community of builders. Finally, we’ve answered the question of what AI is. Now it’s time to ask what it can do—for you, and your business. We call it the era of Deployed AI.
At the heart of Deployed AI is a vision for transforming your business. It’s a clear objective that can bring an entire organization together, aligning teams and engaging stakeholders. This diverse range of perspectives means a deeper understanding of risks and benefits, as well as the cost of change—both practical and emotional. Once deployed, success should be measurable with clear, objective metrics. This encourages an ongoing cycle of refinement, allowing you to continually optimize results while reinforcing trust with your users.
Now, let’s see how some of the world’s biggest brands are using Deployed AI to make their goals possible.
Unilever: Personal Marketing at a Global Scale
Take Unilever, for instance. They’re among the biggest consumer goods companies in the world, with 400 brands ranging from Dove personal care products to Ben & Jerry’s ice cream. Despite their remarkable reach, however, Unilever is a company built on social consciousness and authenticity. So when it came time to align around a Deployed AI strategy, they asked an audacious question, to put it mildly: what if it were possible to maintain true, one-to-one relationships with each of their customers?
…all one billion of them.
In any other era, this would have been impossible. But in the age of Deployed AI, trade-offs that were once inescapable are becoming win-wins—including the age-old tension between global reach and a personal touch. Using a broad range of consumer insights alongside Google Cloud AI tools such as translation, visual analytics, and natural language processing, Unilever is generating insights faster than ever before and gaining an entirely new understanding of what their customers care about.
For example, the Cloud Vision API made it possible to understand the content of photos submitted by Closeup toothpaste customers for a campaign spanning South Asia. In addition, the Natural Language API revealed audience sentiment by analyzing social media comments referencing the campaign. Together, these insights continually reshaped the campaign, giving millions of users a genuine sense of participation.
The vision paid off, and the numbers speak for themselves. The campaign reached nearly 500 million people across multiple continents, generating measurably positive uplift in brand engagement and consideration in the process. And it demonstrated Unilever’s commitment to each customer’s experience, even at a global scale.
Unilever’s story demonstrates the power of a tech-savvy company putting the best of Cloud AI to use. But what about companies just beginning their journey with technologies like machine learning? Deployed AI is about bridging the expertise gap, which is why we’re continually investing in a technology stack that takes the risk out of an AI strategy—sparing you the complexity of implementation and letting you focus on how state-of-the-art tools can solve the problems that matter most to you.
Meredith Corporation: Individualized Curation, Available on Tap
Meredith Corporation is one of the biggest names in media, with brands including People, InStyle and Martha Stewart Living, and an audience of over 175 million readers in the United States. They also own recipe website AllRecipes, where they perfected a manual review process that made content easy to classify and target based on reader preferences. Although highly effective, it was slow, costly, and took years to implement—making it near impossible to replicate for their more than 40 other brands.
This challenge gave Meredith a clear objective for their Deployed AI strategy: build an automated solution with the insight of a manual curation process. Lacking the in-house expertise to do it themselves, however, they turned to Google Cloud’s AutoML Natural Language, which made it easy to generate a custom, ready-to-use content classifier with data they already had. The results weren’t just immediate, but transformative: from day one, the model matched—and sometimes exceeded—the best work of their content review team.
Now, Cloud AutoML has replicated what took Meredith years to build manually, transforming the rest of their properties in a matter of months. The result is tailored content and a consistently elevated experience, impacting tens of millions of readers in a time frame impossible without AI.
Making Trust a Fundamental Part of Every AI Deployment
Finally, there’s the question of trust. Users have never been more socially conscious, and that’s encouraging all of us to make our technology more fair, more accessible, and more secure. AI presents special challenges, however, with bias, privacy and transparency among the most pressing examples.
These are complex problems that demand a mixture of technical, social and institutional solutions. A long journey lies ahead, but it’s one we look forward to sharing with you. We took our first step last year, with the publication of the principles that guide our work in this field. Since then, we’ve greatly expanded our efforts to solve problems and share what we’ve learned in the form of ever-evolving Responsible AI Practices.
At Google Cloud, we’re committed to giving you more than technology. We’re sharing everything we’ve learned, along with the tools, insights and practices you need to deploy it responsibly.
Deployed AI is putting the power to transform your business within reach. It’s about identifying business problems that defy traditional solutions, crafting specialized AIs from Cloud AI components to solve them in ways never before possible, and establishing the results as a new standard across the enterprise. And its focus on real-world metrics means success can be continually measured and optimized in an ongoing cycle of improvement. Over time, this means an ever-growing value, user trust and business impact.
Deployed AI is what’s possible when technologies like machine learning mature, and it’s why we believe the shift from the breakthroughs of AI to the applications of AI will be the most exciting chapter in its history. At Google Cloud, we’re creating a foundation that everyone can build on, regardless of industry or expertise. Let’s create something incredible together.
Source: Google Cloud Blog