Certainly, your company has developed an “AI strategy” that meets the nebulous needs of your CEO and board of directors. That’s great. But, what now? How can you turn that AI strategy into something tangible?
Concord hosted an AI Workshop and panel discussion event featuring Plamen Petrov, Florin Ibrani, and Rajat Relan to discuss how to make AI real for your company. Within the conversation, we covered the AI tool landscape, shared distinct use cases, and learned how to build AI as a platform rather than a project.
In this article, we’ll cover the elements we learned in the workshop and take a look at the journey B2B companies are likely to face when attempting to make AI tangible for the organization.
Is the AI revolution real or merely a passing fad? To answer that question adequately, it helps to go back in time to December 5, 2000.
We’re of the belief that AI, much like the internet, is here to stay. Those who understand AI will have the potential to revolutionize how they conduct business. Granted, there’s a lot of hype and exuberance that is endemic to the tech space. Many enterprises have trialed elements of AI, but avoided ever converting to a real implementation. By and large, there’s a lot of work necessary to define, articulate, and measure business value for AI.
We’re (likely) all in agreement that AI is more than a passing trend. Now for some definitions. Plamen Petrov shares four main areas that define AI:
#1. Artificial General Intelligence. AI can mean Artificial General Intelligence (AGI), which is getting machines to think like people. Tip: you can ignore this one for now – it’s still in the research area.
#2. Machine Learning. AI can mean deep machine learning (ML) to solve hard problems. Tip: you should stay informed on this one – there are usable capabilities and applications evolve rapidly.
#3. Generative AI. AI can mean GenerativeAI (GenAI), Large Language Models (LLM), and Multimodal Models. Tip: you should track this closely – there are “production ready” disruptive solutions here and moving fast.
#4. Enterprise AI. AI can mean Big Tent AI, Practical AI, and Enterprise AI, which takes full advantage of the numerous data-driven tools available in the toolbox. Tip: you should master and leverage this – don’t let ChatGPT and GenAI “crowd out” these time-tested and proven capabilities.
We often think of AI as a linear concept of data feeding into AI and turning into value. In reality, there are many, many layers separating data from business value:
To get it right, we have to focus on the journey of AI in the enterprise, which follows a similar adoption lifecycle to other disruptive technologies:
The first phase any large-scale project is to explore AI use cases and determine if they’re feasible. Your organization must make a judgment on data readiness and see how AI aligns with your business goals.
In Phase 0, it’s helpful to prepare for any temporary disruption in “how things just work” at your business. We recommend working with an organization that can help analyze your business’ readiness and ascertain potential ROI before developing a concrete plan.
Phase 1 allows you to test your solution to validate its business value. We recommend using feedback loops to test and refine your AI solutions to ensure accuracy and potential scalability.
You can also use Phase 1 to ensure the AI solutions meet any regulatory requirements and plug up any security gaps before a wider rollout. It’s far better to test at the beginning where it’s easier to make important changes that may significantly affect your entire rollout.
Phase 1 is important because the decision point for whether you should fully embrace AI typically happens early.
During Phase 2, organizations should adopt and scale the AI tech into core operations of your organization. It’s useful to start with a focused use case and gradually expand its application to see how it impacts various aspects of your business operations, like:
Using automation and AI-driven insights to improve decision making and your customer experience (CX), we expand this across your entire network to improve to improve efficiency and sales on a large scale.
Entering Phase 3 is where transformation happens. As you effectively navigate each phase of your AI adoption, you’ll see successful AI integration within your organization and maximize its benefits. In this phase, AI becomes your competitive differentiator to drive new business models.
If you’re looking for a partner who has experience in getting value out of AI initiatives, look no further than Concord. With data-driven insights, we help you analyze your pilot results to determine AI’s business impact. We evaluate your risk/reward potential and assist you in assessing feasibility, compliance, and long-term scalability. Let’s connect for a customized AI Journey Workshop where we can focus on business value creation, developing an implementation plan, and enabling new capabilities with AI.
We’re here to help you bridge the gap between wild AI expectations and the true value of AI in reality.
Not sure on your next step? We'd love to hear about your business challenges. No pitch. No strings attached.
