Last week I took part in the Google Cloud Next Leaders Connect event as part of a panel on AI for Innovation. It was a pleasure to hear from so many experts across a variety of topics, and one thing was clear: Google continues to push the boundaries when it comes to AI innovation. Google are making AI accessible for everyone. This means pushing the boundaries on research and finding new ways to apply AI to products and services. Through accessible AI, users can find new and exciting ways to solve business challenges and as a dedicated Google partner here at CTS, we can pass this onto our customers. This helps us to work faster in realising their AI ambitions from prototyping through to productising and taking these models into real-time scenarios.
The barriers to AI adoption
More and more businesses are now looking at how they can improve results through adopting AI technologies. Organisations often find at the outset there are certain barriers they need to overcome. The good news is that with the right partner and support, you can surpass these limitations. Let’s take a look at some of them…
Traditionally, the cost of building an AI enabled platform at scale has been restrictive for many businesses. As part of Google’s aims of bringing AI to everyone, you can now keep costs low and forgo that initial investment required through the “pay as you go” nature of Managed services on offer from Google Cloud.
Maintaining the operational side of an AI platform means having to manage a farm of servers, updating software, security, licensing, and dealing with upgrades. And that’s before you consider disaster recovery and failover needs, including maintaining a second data centre! With Google Cloud, most of these problems simply disappear. Your data is protected at various levels and can be stored across regions for high availability. You don’t need to have specialised teams of Operations and Infrastructure Engineers to build and operate your platform.
- Skills & experience
The demand for highly skilled talent in Data Science specialisms is ever growing, so organisations need to find a way to bridge the gap. With Google Cloud, getting started and proving the value of AI in your organisation doesn’t need huge upfront investment in these capabilities any longer.
When building an AI platform, hiring specialists and managing the financial resources takes time. With Google Cloud, you can undertake faster prototyping using a suite of available model types through AutoML, this means you can start to extract even more value from your data, using AI, with a few clicks of a button, creating predictions in batch. You can deploy models to HTTP endpoints and easily integrate with your existing services for online predictions.
The use cases of adopting AI
No matter the industry you operate in, adopting AI can bring exciting changes to your business in a myriad of ways. Whether your goals are to drive productivity or profitability, meet sustainability targets, or make your customers happier, there will be a way in which AI technologies can help you do just that. Let’s take a look now at some use cases…
Sustainability is top of mind for all companies right now and with many setting ambitious targets in the coming years, finding innovative ways to help meet them is more important than ever. AI adoption can help companies with initiatives such as understanding and optimising their supply chain; or monitoring building occupancy for controlling heating and lighting systems, helping to reduce wastage and lower carbon footprint.
- Sales & demand forecasting
There’s nothing worse than a store running out of products that are in high demand! AI can help analyse sales trends, taking into account things like seasonality, to generate predictions about how well an item could sell over a given period, giving the opportunity for store owners to stock up, be ready and never miss a sale.
- Customer segmentation and experience personalisation
Google Cloud has the tools to enable the personalisation of a customer’s experience. Through using data and AI technologies to react to changes faster, businesses are better able to segment and personalise customer experiences in the most impactful way. This provides retailers with recommendations based on customer activity and previous purchases, which can drive conversion rates, sales and customer retention.
- Fraud & Risk modelling
For those in the Entertainment industry, ensuring the safety of your customers and protecting your brand’s reputation are vital. AI can help organisations prevent fraud and reduce risk by looking for key markers in online transactions and customer behaviour.
What’s next for AI?
The possibilities that come with AI adoption are endless and it’s really important to demystify AI in order to drive business adoption. Google is very much at the forefront of doing just that. This is being achieved through platforms and services like Google’s Vertex AI, which provides a single experience for experimenting, versioning, and allows us to seamlessly manage and deploy ML AI models into production environments. At Google Cloud Next ‘22 we saw many exciting AI announcements, such as the next iteration of Vertex AI Vision, for accessing powerful computer vision and image recognition AI. This can further be connected with analytics through BigQuery, to drive real-time business actions. AI capabilities are accelerating at a rapid pace and there’s never been a better time for businesses to start their AI journey.
Interested by what you’ve read? Get in touch with our team today!