In the last two articles in this 3-part series, we discussed how AI priorities will shift in response to the coronavirus pandemic, as well as how companies can further leverage the advantages they have (and can create) to overcome the challenges they are facing in this uncertain time.
This is the final piece in the series — a look at what innovation and strategy leaders need to think about and do to successfully guide AI projects to ROI even amidst the crisis.
They can step up now to become even more relevant than they ever have been, allowing them to secure budget and win market share for their business well after the coronavirus pandemic finally comes to an end.
We begin this analysis with a discussion on how business leaders can step up to lead initiatives at their companies during this tumultuous time.
A Time for Innovation and Strategy Leaders to Step Up
Innovation and strategy leaders don’t need to learn how to code in order to leverage artificial intelligence to help strengthen their companies and emerge from this pandemic. What they do need is a strong context on their own business and a thorough conceptual understanding of AI in order to match problems and opportunities with the technologies that will really make a difference.
A Clear View of Coronavirus’ Impact Today
From the perspective of their own businesses, innovation and strategy leaders will need to have a clear view of coronavirus’ impact today. This will involve conversations with different functional business leaders and executives throughout the company to get an understanding of what kind of impact they’re seeing now and what kind of impact they’re projecting this year.
This is going to be an evolving conversation. Strategy leaders can expect that over the next month or two there will be a lot of revisions to initial ideas about strategy and priorities. But having a clear view of impact that can be built on and adjusted over time through cross-functional conversations across the company is going to be critical.
A Strong Understanding of New Priorities
Innovation and strategy leaders also need an understanding of their new priorities. When they know how they’re company is being impacted by the coronavirus and its economic fallout, they can determine where their priorities lie, whether their priorities are on risks or on opportunities. Many immediate priorities will be on reducing risks.
Leaders should ask themselves and other executives with perspective on different parts of the business:
What is the biggest existential risk that the virus poses for us right now?
In terms of assessing opportunity, leaders should ask themselves and their head executives:
What would have to happen for us to emerge from this crisis stronger than ever and better positioned in the market?
These ongoing conversations should begin now. They should be stored and organized somewhere, and they should be built on consciously over the course of the coming months in order to have a firm base from which a strategy can be built.
It needs to start with these key questions and understandings, and it needs to draw from as many parts of the business as it can. Whoever leads that effort will serve an immensely powerful role in the future of their company. This is among the most important roles in overcoming this crisis.
Basic AI Knowledge
Business leaders need 3 core understandings if they want to contribute to AI projects:
- Conceptual Understanding of AI
- Representative Use-Cases
- How-to Knowledge about AI Adoption
Conceptual Understanding of AI
Business people should have a basic understanding of what AI is, how it works, and how it can be applied to business problems. They don’t need to understand the math and the code, but they do need to understand fundamentals about data and how AI uses it to generate an output.
They also need to be able to discuss AI concepts with data scientists. They need to know basc AI terms, such as machine learning, natural language processing, computer vision, and predictive analytics.
In doing so, they can get a better idea of what their companies’ needs are and which AI approach might meet them.
In addition to a conceptual understanding of AI, business leaders need to understand basic use-cases of AI in their industry. They should have a good idea of how AI could solve a problem at their business and if it’s even the right tool for the job at all.
Emerj’s AI Opportunity Landscape research provides business leaders with the foundation they need to do this. Our clients use our research to discover the highest ROI AI opportunities in their industries and at their companies, allowing them to pick AI projects for key use-cases in their business.
How-to Knowledge about AI Adoption
Business leaders also need to understand how to bring AI projects to life in terms of aligning the business toward that goal. They need to understand that AI may require overhauling data and IT infrastructure, cross-functional team collaboration, and the ability to measure the results of an AI project, even if they aren’t monetary.
AI Knowledge as a Career Accelerator
All of this allows business leaders to brace their organizations for AI adoption, which is often a months long process. AI knowledge will be a strong way to differentiate oneself in the coming years. Business leaders will have the opportunity to shine at their companies if they acquire this knowledge early on in AI’s progression into the enterprise.
The graphic below shows the opportunity that nontechnical business leaders have to differentiate themselves in each phase of AI in the enterprise: Emergence, Adoption, and Dispersion. Most companies in the world are currently in the Emergence phase:
Business leaders have an even greater opportunity during the coronavirus pandemic to turn their AI interest into a career accelerator by showing their companies how AI could help mitigate risks or drive efficiencies at their company and, perhaps even more importantly, how it might not.
Many leaders are going to be looking to AI to solve many of the business problems this crisis will reveal: poor predictive capabilities, unprepared supply chains, and high overhead costs. Business leaders that understand AI will be able to prevent their companies from falling for AI hype and embarking on AI projects that are unlikely to deliver ROI.
Companies can’t afford to be wasteful during this time, and they all too often want to start an AI initiative for the sake of using AI. These projects cost thousands, even millions, and they don’t yield any return.
Business leaders that prepare their companies for the cultural and structural shifts necessary for AI adoption will be valuable in times of uncertainty when AI starts looking like a “bandaid” for problems it may not be able to easily solve.
Much of what is outlined in this section is detailed even further in one of our core resources for getting started with AI and delivering strong ROI from AI projects: Critical Capabilities – The Prerequisites to AI Deployment in Business.
Past Recessions Created Winners and Losers
While the coronavirus pandemic may be unique, times of economic hardship are not. In 2008, the US was hit hard during the Great Recession, and countless companies came up at a loss.
The bankruptcies of Chrysler, GM, Lehman Brothers, Washington Mutual, and many other businesses large and small sent a shockwave through most of the global economy. But some companies weathered the storm and came out winners. We talk about two below: Lego and Domino’s.
Lego: Focusing on the Core Value Proposition
Lego almost went out of business between 1999 and 2004, mostly because the company focused its efforts on projects that were unrelated to their core business model. Instead of manufacturing more bricks and the kinds of traditional Lego sets many of us grew up with, the company ventured into watches, theme parks, and other incongruent ventures.
In some cases, the company was producing Lego sets that cost more to source than they were selling for, and consumers had trouble recognizing the toys as Lego.
Their 2004 change in leadership set the company back on track to focus on producing Lego sets made of bricks that were produced the same way all their others had been for decades.
They reaffirmed their brand and thrived during the Great Recession because consumers again started associating Lego with their bricks, which proved to have longevity in ways other toys did not. Kids could build and disassemble Legos endlessly, and this was a strong value proposition for families that were struggling to make ends meet.
What Lego’s story shows is that one way to survive a significant economic downturn is to return focus to a single value proposition. Lego had already built their brand, and they were straying from it. Returning to what the company was known for allowed their products to reemerge as staples for kids’ entertainment.
AI companies and enterprises that use AI may need to put aside more ambitious, but less proven value propositions during the pandemic and its aftermath.
For example, a financial services company used to working with banks may have begun advertising their enterprise search product to insurance companies. They may want to reel these efforts back to fous simply on the banks they’re used to working with.
Domino’s: Marketing a New Value Proposition
Domino’s story is almost the opposite. Instead of focusing on their core value proposition, delivering pizza quickly, the company repositioned itself with an entirely new but equally important value proposition: taste. Domino’s understood that its pizza had a bad reputation for taste among customers and in the market generally.
The company embraced this with a marketing campaign that garnered them a lot of attention. It changed its recipe and used self-deprecating humor to compare their old pizza to their new one, claiming it was superior in taste. The ads worked, and Domino’s sales soared.
Domino’s was able to essentially pivot their product and marketing efforts. This was a big gamble that paid off.
AI startups in particular are more likely to be able to leverage this strategy to success. They might quickly find out that their usual buyers are unable to spend the way they used to, and they might start marketing their product to other industries.
This, in effect, would be similar to Domino’s recipe change. They wouldn’t be throwing out their product entirely, just marketing it with a new value proposition.
For example, natural language processing vendors could theoretically find it hard to sell their products to financial services during the course of the pandemic, and so they might try to market their product for use in healthcare.
This is just one possible example. Large companies could do the same, but this is likely to be much more difficult with so many more established, less agile workflows in place.
The Bottom Line for Business Leaders
While countless businesses died, in the 2008 crisis, some grew, and some transformed into leaders. Harvard Business Review’s 2010 article has one core lesson for navigating the coronavirus pandemic: that the delicate balance between defense (cost cutting) and offense (investing in the future) is the key differentiator for companies who came out as winners in the 2008 recession.
To quote the article, the best-performing companies post-recession:
…cut costs mainly by improving operational efficiency rather than by slashing the number of employees relative to peers. However, their offensive moves are comprehensive. They develop new business opportunities by making significantly greater investments than their rivals do in R&D and marketing, and they invest in assets such as plants and machinery. Their post-recession growth in sales and earnings is the best among the groups in our study.
During the coronavirus pandemic, innovation leaders can step up by being a guiding light to a better future, pulling together the perspectives that are needed. They will serve the role of getting an objective assessment of the lay of the land and using that with an objective perspective on technology and AI opportunity.
With this, they will align the conversation within the company about where their priorities belong and how they’ll come out of this stronger.
This is a time in which the innovation and strategy leaders that step up will find themselves more relevant than ever. As my friend Dr. Eugene Rotyburg of Fractal Analytics points out, companies need to be prepared for a new normal and they need to find a way to be a part of that new normal at their clients’ companies.
They need to find a way to position themselves a “must have,” a need that clients cannot do without even during times of crisis. Ideally, they want to position themselves as companies that will be relied upon in the face of uncertainty.
The same dynamic applies to consultants. Both small and large consulting firms want to have a seat at the table when large companies reassess their strategies. This will set them up to be lasting partners in a long-term AI transformation, which is one of the biggest economic opportunities for technology consultancies in the next few years.