“In God we trust, everyone else bring data” – W. Edwards Deming
The world is in flux, and the rapid and long-lasting changes that are occurring have hit many enterprises, like butterflies in the chrysalis, mid-digital transformation. In a temporarily frozen economy that will be fundamentally different as it thaws, leaders who are strategically building AI initiatives to take their organization to the next level are asking themselves if they should pause these initiatives, maintain the same pace, or, like Ben Horowitz’s Wartime CEO, even attack the competition by increasing the pace of AI innovation.
Though this crisis is largely unprecedented, we do have data on how successful companies have behaved during past recessions. In a Harvard Business Review study of 4,700 public companies, the most successful companies post-recession (37%) were the ones that balanced cuts in spending with strategic investment in improving operational efficiency, research and development, building assets, etc. Luckily, AI initiatives can help with all of these. Company leaders will need to balance how to move forward with the most pressing of these initiatives while stalling those that will be too much of a drain on resources during the difficult times ahead.
To understand how to do this, here is a snapshot of enterprise needs in this new environment:
What Business Leaders Want Right Now:
- Bring Immediate ROI: Innovation now needs to have an immediate purpose. Whereas AI initiatives in the past had the freedom to be slightly experimental or bring a return on investment over the medium-to-long-term, today’s AI initiatives must bring immediate value. This will be the case for at least the next several quarters as enterprises come to terms with the new normal.
- Increase Resilience in the Supply Chain: Supply chains have faced short-term COVID-19 closures, but even after factories reopen, there could be tariffs and border concerns that limit supply. Everyone wants to optimize resilience by establishing more local manufacturing capabilities.
- Optimize Trust: Times of uncertainty highlight the value of customer trust, but with international and supply chain suspicion abounding, trusting your business partners and suppliers is a major concern for the enterprise.
- Returning to the Office Safely: As we begin to move towards normalcy, enterprises want to maximize employee safety and comfort while returning to the office. There could also be significant disruption as many companies will mirror Twitter and Facebook by permanently staying remote.
The New Code for Companies
Normally conversations around AI deployment in the enterprise have been focused on three words: transformation, innovation, and disruption. However, in the wake of COVID-19 and with the new business priorities outlined above in mind, these words have shifted to survival, resurrection, and reset. If this is the new code for companies, what does AI mean in this phase?
Firstly, there will be a different type of trend data.AI can help companies identify what is trending and what will be the next big thing, but now there is a new focus: what will go out of fashion and what products and services will lose demand right now? AI can help forecast this data and make predictions to help offset losses.
Secondly, the “segment of one” will become increasingly important. In relation to COVID-19, it is extremely important to understand each person in all of their individuality to make the correct healthcare decision. Similarly, we can apply data analytics and AI personalization to make better business decisions. Increasingly, personalization will be the standard to which customers hold brands, and brands will need to understand how to use customer data to personalize their experience.
Of course, this has privacy implications.However, an Experian report suggests that 87% of customers find it acceptable for brands to use their data to personalize interactions, as long as it is relevant to them. We might find that COVID-19 has made this number even higher.
The Future of Trust
Data and analytics have a role to play in the evolution of trust across just about every segment of society, from governments to businesses to individuals. The ways in which trust is established have been changing for years, but COVID-19 really accelerated these trends.
This has pushed us towards the relationship-based model of trust. Like the relationship with a long-time family physician, you trust these types of relationships because of accumulated information over time. Doubting the safety and reliability of globalized supply chains, businesses and manufacturers are building resilience by turning to local suppliers and networks who embody this relationship-based model of trust. They are willing to compromise economies of scale to build these local networks.
Another model of trust is the authority or hierarchy model. You trust the government or your boss because they are in a position of authority over you. For instance, China’s strong response to COVID-19 derives from this model of trust that they have developed with their citizens. This model enables much faster responses to crisis, but it is not suited to all contexts.
The final model is the democratic, data-based model. Using the power of data and analytics, nothing is hidden. It solves the problem of information asymmetry, where suspicion derives from disparate levels of information between individuals. For instance, it is said that the origin of the handshake was to voluntarily show that you were not carrying a weapon and thus had peaceful intentions, which builds trust explicitly by solving information asymmetry.
The changing role of trust is creating business opportunities, specifically for the data-based model. As we move towards an increasingly data-rich environment, cybersecurity is a huge area for growth because we will need to not only share data but protect it. Algorithms will rise to the fore as AI and ML better equip decision-makers to select data-informed solutions that can be trusted by everyone. These solutions will not just build trust for the sake of trust alone, they will build trust with customers, partners, and even stakeholders within the organization, driving business outcomes and efficiencies.
What Next?
For companies asking themselves what to do next, here are three criteria that they can use to evaluate an AI initiative in this new environment:
- Focus on initiatives that increase your resilience
- Focus on initiatives that increase trust
- Focus on initiatives that increase the safety of the system
Any initiative that you pick up should be evaluated against these key parameters. Ask yourself, is this initiative helping me increase resilience, trust, and safety? If the answer is yes, then go about defining the problem set and use case in alignment with some of the pressing business needs and AI trends sketched out above.
