How to accelerate your path to AI
Software vendors that are looking to accelerate their path to AI need to take advantage of the AI already in analytics platforms.
Gartner believes that the future of analytics is augmented. That is, analytics will be AI-driven and all end-to-end use cases will be automated. I also believe it won’t be long before analytics is no longer on our desktops - instead it’ll be embedded in applications. We’re already starting to see this happen, which means any software vendor that wants to take advantage of AI through analytics has no time to lose.
The biggest AI mistake you can make right now
At the moment, some independent software vendors are starting to tinker with AI and trying to work out how they can make it work for them. If you’re an independent software vendor, the biggest mistake you can make right now is to start investing in AI capability in-house. That’s because you don’t have the time to catch up to the bigger players who are already well down the software development path.
Any new form of software development goes through three phases. It starts off being the domain of expert organizations who handcraft tools in-house from scratch. Some of the leaders in AI right now have done just that. Google and Amazon have spent a lot of money on data scientists and other experts to create their AI software in-house. So if you’re just starting to think about letting your Dev team spin up their own data science organization, you’re too late. It’ll take too long to develop your AI capability and soak up all of your profits before you can catch up to the rest of the market.
Many of these mega-vendors are already in the next phase of software development. This is where they take their R&D and create a set of tools or platforms that are generic enough to apply to multiple problems. They’ve taken the risks so they can define the market and profit from it. Many businesses are already able to use AI through tools like TensorFlow from Google, the AWS stack, or IBM's Watson.
AI is going mainstream and solution-specific
This has paved the way for entrepreneurs to come in and build products that solve more specific problems. This is the phase we’re entering now - AI is going mainstream. Rather than using a generic platform, software vendors can now embed specific AI into their own applications. This process is seamless to the end user and allows software vendors to deliver AI capability into their workflows.
The biggest difference between the development of AI and other software platforms is the speed of the transition. While ERP platforms took decades to reach this stage, AI has probably had the fastest transition from in-house R&D to mass market that we’ve seen in software development. I believe this is because organizations realize that AI can really give them a competitive advantage, so there’s no time to waste.
The biggest AI opportunity right now
The biggest opportunity for you right now is to accelerate the process of bringing AI into your product at the lowest cost possible. Rather than investing in creating your own AI capability, get to market much quicker and cheaper by purchasing a black box that someone else has built and embed it into your own application. For example, if you've got a data-rich application then embedding an innovative analytics tool like Yellowfin will accelerate your path to AI. Why would you incur the cost, complexity, and ongoing maintenance of building AI yourself when you can buy it off the shelf?
AI capability could give your software a new module that you can upsell or use to attract more customers. It can also potentially attract more funding, as the VC market is eager to invest in businesses that have AI capability.
While it may be tempting to build your own AI capability, it’s unlikely that you’ll get any competitive advantage from it. The reality is that the use cases you’re building are probably similar to those already in the market. There are specialist vendors who have already built toolsets that you can plug directly into your application. This will enable you to accelerate your path to AI faster at a lower cost, giving you the opportunity to profit from it. The trick is doing it before your competitor does.
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