AI Profit Playbook: 6 Insider Secrets from Global Tech Giants

Artificial intelligence or AI has taken the world by storm. In the race to keep up with competitors, many companies are jumping onto the AI bandwagon. But many don’t seem to have a concrete game plan for monetization. Beyond the hype, are there real AI monetization opportunities? What are the crucial factors for successful AI businesses and viable models? And what can companies expect on the path to AI's real payoff?

At the 2024 ATxSummit held in Singapore, CNA Presenter Dawn Tan moderated a panel discussion titled “The Bottom Line on Gen AI – Where is the Top Line?” Tech leaders from Google, Samsung Electronics, Alibaba, Agoda, and DataRobot shared their knowledge and insights on how AI can be used to win over customers and maximize profits and growth.

Now, I took 40 minutes of your time and saved it by summarizing the best bits of this insightful discussion. Grab a coffee, sit back, and let’s get into the nitty-gritty of how AI can bring in the big bucks, straight from the mouths of these tech giants. Spoiler: it's not just about having the fanciest tech toys.

The Hype vs. Reality

Dawn Tan kicked things off with a reality check: AI is booming, but can it really deliver on its money-making promises? The answer is a resounding yes—but only if companies have a solid strategy and aren’t just jumping on the bandwagon. She shared a quote from Mr. Gupta, CEO of Amberflow:

"There are too many companies that are showing up to this gold rush without a shovel. The urgency is there, but is the strategy in place? How can these companies actually make money from these new applications?"

This quote sets the stage for understanding the critical importance of having a well-defined strategy for AI monetization. The discussion that followed revealed six insider secrets from some of the top tech leaders on how this can be achieved. Let's dive into these valuable insights and learn how to turn AI potential into a profitable reality.

Samsung’s AI in Everyday Tech

Dr. Joohyung Lee, Executive Vice President of Samsung Electronics highlighted their focus on enhancing customer experience through AI. They integrate AI into their hardware for features like real-time translation, AI-enhanced picture quality in TVs, and smart fridges and washers.

These innovations improve privacy and efficiency, showcasing Samsung's commitment to customer-centric AI applications. For instance, Samsung’s real-time translation runs entirely on the device, protecting user privacy by not uploading data to servers, which also saves on costs and reduces latency. Law enforcement agencies even purchase Samsung devices for secure communication. Talk about a tech win-win!

Agoda’s Inside-Out Approach

Dan Zalverg, Chief Technology Officer at Agoda discussed their strategy for AI, which emphasizes starting from within. Agoda uses AI tools internally first to identify and resolve any issues before they are rolled out to customers. This “inside-out” approach ensures the AI is reliable and enhances the customer experience by minimizing inconsistencies.

Their method involves a cautious, iterative rollout, beginning with internal testing to perfect the tools, thereby avoiding the pitfalls of a rushed deployment. The key takeaway from Zalverg’s approach is clear: don't rush AI to market—test, learn, and refine first to ensure optimal performance and user satisfaction.

Google’s Three AI Concerns

Moe Abdula, VP of Google Cloud shared three major obstacles in AI deployment: hallucinations, deep fakes, and copyright issues. To address hallucinations, Google employs grounding techniques to ensure AI responses are anchored in real, verifiable data. To combat deep fakes, they developed Sense ID, which verifies the authenticity of images and videos, now extended to cover audio, thus protecting brand integrity.

For copyright concerns, Google incorporates stringent copyright measures and indemnification clauses to prevent legal issues. Additionally, their collaboration with Nvidia and the introduction of the model garden provide a robust, multi-model AI ecosystem, allowing for diverse and secure AI model usage.

Alibaba’s Open Source Strategy

Selina Yuan, President of Alibaba Cloud Intelligence International, talked about how Alibaba is excelling in China with 80% of tech businesses using their cloud services. They have open-sourced large language models to make AI benefits accessible to a wider audience.

They focus on enhancing efficiency and improving user experiences with AI, making manual tasks easier and offering innovative solutions like text-to-music in the metaverse. The message? Open collaboration and resource sharing can drive massive AI innovation. Alibaba's cloud services support a significant portion of AI-driven processes in China, showcasing their leadership and innovation in AI.

Datarobot’s Flexible AI Ecosystem

Jay Schuren, Chief Customer Office of DataRobot emphasized the necessity of flexibility and diversity in AI strategies. DataRobot leverages a variety of AI models and providers to ensure cost-effective, fit-for-purpose solutions. They have built a robust evaluation framework for assessing AI models' performance, cost, and scalability.

Schuren stressed the importance of operationalizing AI models to provide ongoing value and adaptability. This approach ensures businesses can integrate AI into their processes effectively, manage costs, and remain agile as technology evolves, highlighting DataRobot’s commitment to providing sustainable and adaptable AI solutions.

Collaboration is Key

Across the board, the panellists agreed that collaboration—whether within the tech community, with customers, or with governments—is crucial for AI success. Samsung collaborates with Google and Qualcomm to enhance their devices, while Google and Nvidia bring shared tech to the public cloud. Alibaba’s open-source efforts and Google’s model garden are prime examples of how shared resources and knowledge can accelerate AI development and deployment. Samsung's collaborations have led to innovative features like enhanced search experiences on their devices, while Google's partnerships bring advanced computing resources to the public.

Practical Tips for Companies Starting with AI

1. Start with the Customer: Understand the pain points and frustrations that AI can solve.

2. Iterate Internally First: Develop and refine AI tools within your organization before customer rollout.

3. Ensure Accuracy and Reliability: Use technologies to mitigate AI’s potential errors and biases.

4. Stay Flexible: Don’t lock into a single AI model or provider; keep options open.

5. Collaborate Broadly: Work with tech providers, developers, and even competitors to enhance AI solutions.

6. Focus on Privacy and Efficiency: Ensure that AI applications protect user data and operate efficiently.

Final Thoughts

The panel ended with a forward-looking note: AI is here to stay, and its potential is vast. Companies that are willing to challenge the status quo, invest in robust frameworks, and prioritize customer experience will lead the way. So, grab that metaphorical shovel, and start digging into the AI gold mine with a strategic, collaborative approach.

For those of you diligent enough to want the full scoop, you can check out the full video here.

And there you have it! The essentials from the AI monetization panel, wrapped up with a bow. Remember, the real gold lies not in the technology itself, but in how creatively and effectively you wield it. The future belongs to those who dare to innovate and redefine what's possible.

See you in the next one.

Aaron