In the five years leading up to 2022, the implementation of AI has more than doubled, incorporating advancements in various functions such as facial recognition, understanding natural language, and robotic process automation. However, recent data from a McKinsey survey indicates a stagnation in the percentage of businesses utilizing AI across sectors, dropping from a peak of 58% in 2019 to 50% last year.
Ankur Agrawal, a McKinsey companion specializing in advising healthcare officials, likens Generative AI and similar systems to swimming: the true learning happens when one immerses themselves in the ocean.
Agrawal proposes that C-suite executives should approach AI strategically, emphasizing that while productivity is crucial, significant returns often stem from long-term tactical applications that shape the company’s strategic direction.
The primary challenge for businesses venturing into AI deployment for the first time, as highlighted by Agrawal, lies in setting up a cross-functional group to identify suitable business cases for AI utilization. He underscores that the obstacle lies more in the realm of business strategy than technology. Once the foundational technical infrastructure like data systems and cloud computing is in place, Agrawal recommends creating use cases that promise short- or long-term value.
Boston Consulting Group advises consumers to follow a 10-20-70 formula to assess the enterprise value of AI, allocating effort as follows: 10% on machine learning model development, 20% on implementing top-tier data and technology, and 70% on innovating business processes or transforming operational methods.
For businesses new to AI exploration, Sylvain Duranton, managing director at BCG, suggests initiating a task force involving IT and HR functions. Evaluating available products and budgeting for deployment costs are crucial steps due to the potentially high expenses involved.
Duranton stresses the importance of evaluating functions where AI implementation could lead to at least a 50% increase in productivity, while also considering areas where the benefits, though less pronounced, still hold significant value. He warns against the common mistake of underestimating the potential impact of AI.
Intuit’s Chief Data Officer, Ashok Srivastava, emphasizes the significance of strategic planning before substantial investments in AI and data. Srivastava asserts that achieving value for customers involves a holistic approach beyond just AI, encompassing the entire system, data analysis, and related components.
Dr. Robert Blumofe, Akamai’s Chief Technology Officer, underscores the pivotal role of quality data in unlocking the value of AI. He highlights the distinctive nature of relational AI, citing the rapid adoption of OpenAI’s ChatGPT by millions of users within a short timeframe.
While executives show increasing interest in generative AI, concerns about implementation persist. According to EY, developing and executing an AI strategy remains challenging due to uncertainties surrounding Generative AI.
Weber Shandwick’s Chief Development Officer, Chris Perry, notes that business leaders are initially perplexed and sometimes frustrated by the rapid advancements in relational AI models. Perry likens the situation to deciphering the implications of a newly released genie.
Weber Shandwick has been instrumental in guiding numerous clients in understanding the implications of AI for their businesses. Perry observes a shift from confusion to excitement among executives after utilizing the company’s online lab for assessments, scenario planning, and message testing.
The use of conceptual AI algorithms to generate text, images, and sounds can evoke a sense of eeriness for some individuals. Sharon Mandell, Chief Knowledge Officer at Juniper Networks, describes this feeling as more animal-like due to the vocabulary employed.
Nationwide’s Chief Technology Officer, Jim Fowler, emphasizes the collaborative relationship between humans and AI systems to enhance customer service. Nationwide ensures human oversight in processes utilizing conceptual AI models to address potential errors.
Nationwide’s business unit officials are tasked with leading digital strategies that incorporate AI applications.
Deloitte’s Will Bible advises integrating conceptual AI into existing large-scale technology investment programs. He recommends a commission-based approach to AI adoption, involving multiple perspectives from sales, operations, risk management, compliance, and legal departments.
Chris Griffin, Managing Partner of Change and Technology at Deloitte, stresses the collaborative nature of AI integration, emphasizing the need for diverse viewpoints across teams to ensure successful implementation.
Griffin highlights ongoing discussions among consumers and boards regarding AI integration, indicating a sustained focus on this topic in the business landscape.
