Opinion Getting started with artificial intelligence using the Value Pyramid
With artificial intelligence taking center stage, business leaders across all industries are discussing - and considering - the implications of automation and personalization. The excitement levels have risen as more executives begin to see the opportunities that AI can bring when differentiating their offerings, personalizing their services, designing their products, and optimizing their operations.
Source: Suffiyan Syed
With this interest comes the biggest question: How do we implement AI in a natural way, both for our people and our customers?
A contextual understanding of AI and its relevance combined with a strong point of view and a good data science team (to execute on your vision) is only half of the battle. The biggest, ongoing obstacle that executives face is their ability to architect a process for applying data intelligence to their business and decision making. Executives require a strategic approach in order to invest in the right AI projects.
Spanning cost reduction, increased efficiency, enhanced insights and customer engagement, and (new) business automation, the AI Value Pyramid is a set of guidelines for executives looking to invest in AI, but unsure where to start. Executives from across various industries can use these guidelines to explore opportunities for infusing AI into their own organizations.
Reduce costs by identifying recurring activities that can be automated using Machine Learning.
This is the easiest way to infuse AI into your organization (and justify the investment). In almost every large business, there are processes that require a human mind to take in data and perform a very simple, mental calculation. These simple tasks require various levels of human judgment and are not suitable for automation using traditional, hard-coded rules. Methods in Machine Learning, however, thrive in this space. They consume data and approximate human reasoning to either greatly reduce the human intervention needed or eliminate it completely – thereby freeing up those human resources for more valuable activities.
Identify opportunities across your service journey that impact your business at scale.
In the second layer of the pyramid, try to be a little more adventurous with AI. Look for critical moments that can be optimized further through the application of Machine Learning. For instance, allow the Machine Learning approach to increase sales and reduce churn by categorizing consumers/users via richer, more refined segments – rather than your typical “Millennial Moms” persona and the like.
When your organization is ready to make a stronger commitment to data, you need to focus on acquiring the right data.
Building an AI roadmap that embeds the right receptors across your customer journeys allows you to better understand your customer and explore how he/she uses and interacts with your service. This rich data will allow your data science team to dig deeper and find meaningful patterns that you can use to engage with the consumer in new ways.
For example, we architected a strategic roadmap of AI-based solutions that enabled a top-three, global mall operator’s retail ecosystem to come to life. The mall operator saw which stores were more successful and how they affected each other; integrated the digital solutions necessary for seamless, mall-wide experiences; and, perhaps most exciting, used the data to predict and plan for day-by-day behavior. Something like this simply wasn’t possible before Machine Learning.
Tap into enhanced insights and thoughtful execution for truly meaningful customer engagement.
Chatbots are on the rise, but there is still minimal consumer understanding and a lack of brand discovery across platforms. While building a chatbot can definitely aid in reducing cost, increasing efficiency, and enhancing insights about your customers, the right context that accentuates the existing customer experience is integral to its success.
Identify journeys of differentiation across your business that you can automate.The higher you’re able to elevate your organization in the AI Value Pyramid, the more mature it becomes in an AI-first world. At this stage, your organization should have a mature data practice; an existing process for acquiring data, translating it into insights, and delivering it in execution; and a strong customer feedback loop. The combination of these is what enables business automation.
Allow AI to bridge the gap between data, industry, and new business.
Applying AI to the automation and differentiation of current processes is great, but the genius of AI is realized when you can use all the incredible insights that you’ve uncovered to recognize opportunities, validate need, and spin off new business initiatives. This requires an advanced and experienced data practice that's able to glean insights from multiple sources of data and formulate those insights into rich implications applicable to the industry or business at hand.
By infusing AI into their organizations and quantifying return, decision makers will be able to focus investment in specific areas. In fact, we built the AI Value Pyramid to help executives do exactly this – cultivate a strategic approach that shows the impact of investing in the transformation of their organization into one that puts AI first. These leaders will be the ones that spearhead AI’s shift from potential to execution, educating their peers and audiences along the way.