Machine learning (ML) and artificial intelligence (AI) applications are booming in the corporation world. While algorithms aren’t always replacing humans, they are usually changing the way we work. No leader is safe from the rapid change we are seeing in the age of algorithms. Businesses are transforming at rapid pace and there is no time to dilly dally. Learn how to make use of algorithms to build on your human skills or risk being replaced entirely.
Leadership teams tend to have innate biases for certain asset types, and that these preferences drove business model. Like a good driver, a leader needs to know when to speed up to catch the competition, when to shift investment into the right kinds of capital, and when to refuel with new skills, mental models and board members. Just as the human genome offers the prospect of personalized medicine, the value genome offers the prospect of tailored capital editing—refocusing companies on high-value, scalable assets.
AI-based platforms are quantifying and getting value from you by gathering your contacts, your ideas, your skills, your free time, your shopping habits and even your very genes. The tradeoffs here are not so clear. Companies win big using your data. So, on top of worrying about whether or not AI will steal your job, you must also worry about AI stealing your time, information, ideas, relationships, and more. AI is breaking us down into our piece parts, and using them up.
There is an intensively competitive market for artificial intelligence and machine learning specialists. Many companies first attempt to hire Ph.D.-level data scientists with expertise in AI algorithms and feature engineering. Some analysts have even equated “AI talent” with such researchers. However, AI talent goes far beyond machine learning Ph.D’s. Equally important and less understood are the set of talent issues emerging around AI product development and engineering. Most firms have not filled these roles, and their AI projects are suffering as a result.
According to Pareto Principle, also known as the 80/20 rule, only a few decisions create the bulk of corporate value. The question is: do you know which decisions are important in today’s digital and platform economy? Do you and your board know the vital few decisions that will truly determine whether your business is bad, good or great in age of technology, platforms, networks and machine learning? And if you do, how much capital and leadership effort is being devoted to the most important 20% versus the remaining 80%?
How does a company transform its business model midflight, while at the same time competitively operating legacy businesses in order to provide stability and cash flow? AI can help you better understand what is truly driving value in your company. This is hard work, because it requires you to be data driven. Once you get your team and tools together, it’s time to begin the journey of real transformation using AI-driven insights to power platform business models.
With the advent of the software, high speed communications, AI and the internet, there are new horizons of innovation, which bring new competitive advantages to those that embrace them. Every company needs to have a strategy for all three horizons: continue to optimize the core business, but also create subscription-based digital offerings and build a digital platform with network effect. Failing to do so will mean yielding market value, customers, and employees to companies who do.
No leader should deploy intelligent and autonomous applications without a thorough understanding of how the system works, from the variables used for analysis to the key outcomes tracked for success. Without the right data and the proof needed to recommend and execute actions, the system is actionable. Leaders cannot, and will not, move to a model of intelligent applications without the trust and transparency provided by the education and monitoring piece. But when the five components of AI are integrated and made easily available to leaders, AI can begin to guide strategy in all types of organizations.
The Platform business model is clearly today’s economic winner. Rather than seeking to control the means of production, platform companies focus on the means of connection, connecting and facilitating the interactions between buyers and sellers, suppliers and consumers, or even just friends and families. And they generate revenue by collecting a “toll” from each interaction on their platform. Platforms gather data and use to feed artificial intelligence that helps manage the platform, an essential step due to the scale of due to scale of their organization.