As Generative AI transforms industry at a fierce pace, organizations face important challenges. How do you build a product that not only insights into today's users, but also drives valuable, reliable, and competitive AI? The answer starts with resilience as a principle of new design.
Unlike previous products, systems, and software development cycles, products followed predictable patterns, so AI-powered solutions introduce unique uncertainties. Models can drift in unexpected and unproven ways during development, generate unexpected output, or fail. This introduces new vulnerabilities. SMART organizations are aware of this and are changing the way design sessions are conducted. Product design resilience (and broader organizational robustness) is a new strategic imperative for AI initiatives. And one of the key dimensions of resilience is getting the design right. This is a new kind of challenge.
New development paradigms
Traditional product development assumes that if the product is built correctly, it will function consistently. AI products vary. They learn, adapt and sometimes surprise us with their output. Customer Service Chatbots can work perfectly for several months before suddenly generating inappropriate responses. The recommendation engine may start to distort the response depending on the audience. This is an issue that may not be obvious on small scales, but it becomes clear as you scale. Inherent unpredictability means resilience is fundamental to determining whether an AI product is a strategic asset or costly liability.
Modern resilience requires a clear look at systems, processes, risks and strategies. What does your organization represent and how will the promises of that brand appear in this new set of products and solutions?
Actual recovery
Resilience at the organizational level is the ability to survive and thrive when disruption disrupts business operations and expectations. This goes far beyond the implementation of recovery and redundancy plans. It means thinking and understanding interdependencies, focusing on security, infrastructure and data, thinking and understanding investments continuously, and, of course, ensuring that your strategic plan is in place for known challenges. In the age of AI, it also means getting core design and governance right.
Incorporating resilience into organizational strategic thinking and product design requires a new kind of mindset.
1. Know that you stand as a problem of grounding and early design, especially when agent AI appears in mainstream practice: what is your brand's promise, what is your purpose and value, what is your defined guardrails and boundaries, and what are your metrics for your success?
2. Look for vulnerabilities: Hunt them with the willingness to clearly see the vulnerabilities so that they can be dealt with them as in advance as possible.
3. Look for opportunities: What are the opportunities to move forward, not only to recover operations, in the face of predictable disruption? What can you rethink, redesign or rebuild?
4. Approaching risk as a strategic function: move beyond mitigation to calculate risk taking and rapid adaptation. Makes active sports more than compliance activities a risk.
5. Make strategic investments to navigate foreseeable disruptions and challenges:
- a. Basic digital and physical security, data governance and workforce upskills;
- b. Impact on ecosystems, business models, customers, employees and supply chains
- c. Data, security, energy, banks, misinformation, regulatory systems, challenges for bad actors, and
- d. The process for predicting and handling urgent risks and ongoing leadership training.
6. Use AI to look around corners and shift your perspective. Use AI tools to pressure your testing strategy and detect vulnerabilities and opportunities.
The decision on whether to accept AI in its products is already being made by the power of the market. The question is how to build a resilient organization that designs AI products and processes that allow them to thrive in an uncertain world. Resilience to organizations, products, and methods can make all the difference.
