Build a Post-Pandemic AI Strategy for Resilience, Recovery
Expectations are high for artificial intelligence’s ability to prime businesses for post-pandemic resiliency, and rightfully so. Research firm IDC predicts that global spending on AI will double over the next four years, growing to more than $110 billion in 2024. Research from Accenture also shows that companies that successfully scale AI achieve nearly 3x the return on investment and a 30% premium on key financial valuation metrics.
While the hype around this technology is not new, the COVID-19 pandemic sharpened the contrast between those who have professionalized their AI capabilities to scale across the enterprise, and those who have yet to tap into the full value of their AI investments. In an attempt to recover and achieve sustainable growth beyond 2021, it will be crucial for companies to embrace evolving AI capabilities by transforming into an intelligent enterprise that embeds analytics into the core of its operations.
Stages of AI maturity
As we enter a new era of technology, work and life, there will be increasing pressures for IT leaders to quickly scale AI and its techniques -- including machine learning, natural language processing, knowledge representation, computational intelligence, and more -- to enable an automated, intelligent and insight-driven organization. Our research shows that most C-suite executives (84%) believe they must leverage AI to achieve their growth objectives, but most do not know where to start, with 76% of execs reporting that they struggle with how to scale.
If you’re still in the early stages of AI maturity, you’re not alone. In our experience, most companies (80-85%) are still in the initial proof of concept phases, resulting in a low scaling success rate, and ultimately a lower ROI. Often IT-led, these small-scale efforts tend to be siloed within a department or team and lack a connection to a business outcome or strategic imperative.
In parallel, we’ve seen that very few organizations (<5%) have progressed to the most advanced point of AI sophistication. These companies have a digital platform mindset and create a culture of AI with data and analytics democratized across the organization. Businesses that are industrialized for growth are consistently scaling models with a responsible AI framework to promote product and service innovation. Our research shows that strategic, wide-scale AI deployment will enable competitive differentiation, correlated with significantly higher financial results.
Putting principles to practice
To scale effectively -- no matter where your company currently stands in its AI journey -- IT leaders and their teams must professionalize their AI approach, categorizing AI as a trade with a shared set of principles and guidance.