Why your AI plans will fail (and how to shift the odds in your favor with AI Readiness)
Artificial Intelligence is forcing companies to grapple with how to adapt to a world where accessing near human intelligence no longer exclusively means hiring, training and compensating a human employee. Today, generative AI has few use cases that have dramatically altered some roles, and many where it can drive higher productivity and superhuman quality.
Within 5 years, we believe that organizations will be able to deploy nearly unlimited human level AI at a low cost. This shift to intelligence abundance will fundamentally change how organizations accomplish their missions, what jobs exist and what tasks humans perform. Companies that begin incorporating AI into their operations now will be able to take advantage of this change, and companies that do not will underperform at best.
We’ve been helping executive teams understand the AI landscape, incorporate it into their strategies, and structure experiments with impactful use cases. While many are quick to say “Let’s go”, we’ve found that like any change, the appetite and ability to embrace AI within the rest of their organizations varies considerably. We’ve created an AI Readiness framework to help leadership teams evaluate their organizations capacity for AI adoption, so that their strategy has a better chance of being implemented successfully.
We define AI Readiness as the following factors:
Readiness Drivers
Strategic Alignment: The alignment between business and technology strategies, existing strategic investment in new technologies, leadership buy-in.
Propensity to Innovate: Available R&D budget that could be (re)allocated to AI and the freedom given to teams to experiment and launch pilots.
Infrastructure Robustness: Consider the agility, speed, strength, and security of existing IT infrastructure.
Readiness Detractor
Organizational Inertia: Your org’s resistance to change, including bureaucracy, old technology stack, and complacency.
Readiness Factors
Strategic Alignment
Represents how closely the enterprise and technology strategies are interrelated, to what degrees the CIO and/or CTO drives and supports leadership priorities and how line leaders view the CIO org as able to accelerate their results. Key measures of this are how much time CIO/CTO gets on ELT/board meeting agendas, size of budget relative to other functions and the personal relationship between the technology leader and the CEO.
In our work with technology companies, CEOs see these leaders as the key partners to their success and thus are often able to move faster. Conversely, in organizations where IT is seen as essentially a support function, leaders must reframe their thinking around the CIO org and often requires a new leader or extensive trust building.
Propensity to Innovate
Is fundamentally a measure of the culture of innovation an organization has and there are 3 key factors that underpin that culture: autonomy, resources and mindset. Innovative organizations give teams the freedom to pursue new products/solutions, have budget allocated to innovation that could come from anywhere within the organization (not just R&D org), and view failure as an accepted part of the process.
Innovative companies have a history of funding pilots from different parts of the business and their company lore is littered with fast, low cost failures that people only remember as opportunities to learn, as well as experiments that were successful and scaled when ready. Companies we work with that struggle with innovation often have employees who worry more about “looking bad” due to a failure, rather than recognizing the opportunity to create something new.
Infrastructure Robustness
Captures the entirety of an organization’s IT capability–whether it is constantly improving on core processes, has a user-centric ethos, and maintains an advanced infosec posture. Key business activities are frictionless from a technology perspective, the IT org takes in user feedback and consistently uses employees as beta testers. The CISO org has top-level talent and is constantly pushing the limits of threat detection and prevention.
Leadership teams can quickly understand their company’s IT Robustness by asking a few frontline employees. If the technology stack inhibits, rather than accelerates employee workflows, then your infrastructure likely has not received the resource and talent investments needed.
Organizational Inertia
Reflects the mindset within the organization regarding change. Organizations typically don’t start with high levels of inertia, their inertia is earned over time, ironically enough, through their success. That success leads to complacency and bureaucracy that is created to replicate and protect that initial success. If employees can’t identify the individual factors that led to success, they are afraid to change any process because it could break the system–leading to a “this is how we’ve always done things”.
Organizations with high inertia live with aging tech stacks that don’t support core processes, have long decision cycles and a culture of caution around change that causes delays. Organizations with low inertia are paranoid that their success won’t last if they don’t improve, and thus are willing to disrupt themselves. Their culture encourages people to openly and willingly question the status quo–and those questions lead to change and continuous improvement. Low inertia enables innovation to move forward unencumbered and increases chances of success provided the other factors discussed are present too.
AI Readiness and You
Taken together, Strategic Alignment, Propensity to Innovate and Infrastructure Robustness represent the positive thrust of an organization’s AI Readiness which is then inhibited by Organizational Inertia. Leadership teams can do 2 things with this framework–they can use these factors to scale their AI strategy to their team’s AI Readiness today AND they can focus on improving the underlying factors to build AI Readiness for the future.
In the not so distant future, organizations will operate in a world of intelligence abundance rather than scarcity. By beginning AI experiments that are aligned to strategy and feasible today, while building for the future, leadership teams can position their organization to compete and win as AI advances rapidly continue.
