Monday, March 27, 2023

Why Businesses Are Still in The ‘AI Adolescence’ Phase

By Swapnil Mishra - September 07, 2022 4 Mins Read


AI maturity comes down to mastering critical capabilities in the right combinations—not only in data and AI but also in organizational strategy, talent, and culture.

The AI transformation is occurring much faster than the digital transformation, because early successes have increased faith in AI as a value driver. There is a significant incentive to move rapidly. According to new research from Accenture, ‘The art of AI Maturity’, 63% of 1,200 companies were identified as “Experimenters,” or companies stuck in the experimentation phase of their AI lives.

They risk losing money since they haven’t fully tapped into the technology’s potential to innovate and revolutionize their industry. The companies with the highest advanced AI are already using this money. The “AI grownups,” also known as Achievers in the research, are a small group. Yet, they are reaping significant benefits: They accelerate revenue growth by outperforming their competitors in AI. The level of an organization’s mastery of AI-related capabilities in the proper mix to produce a high performance for customers, shareholders, and employees is referred to as AI maturity. The ability to master a set of critical competencies in the proper combinations—not just in data and AI but also in organizational strategy, talent, and culture—determines AI’s maturity.

AI adults master key capabilities in the right combination by having command of the technology itself — including data, AI, and cloud — as well as their organizational strategy, responsible use of AI, C-suite sponsorship, talent, and culture. 

Understanding what prevents immature AI users from developing makes sense in light of this. Here are few things organizations can do to accelerate AI maturity:

 Innovation emboldened by leadership

Compared to 83% of Achievers, only 56% of Experimenters had CEO and senior sponsorship, indicating that leadership support is the first step toward AI maturity. Additionally, Achievers are four times more likely than Experimenters to put in place systems that facilitate internal idea sharing and question-asking with ease. A global digital platform utilizes AI and generative design to produce autonomous buildings that fit together as one illustration of innovation encouraged by leadership.

Also Read: Leveraging Low-Code to Level-Up Total Experience (TX)

Investing in their team members

The lack of AI-trained staff hinders experimenters. Additionally, they haven’t yet invested in training that enables their staff to become AI-literate. Experimenters should retrain present team members on AI to succeed with the technology.

Integrating AI across the enterprise

A foundational AI core is absent from 75% of the firms evaluated, even though AI has been included in their business strategies and cloud plans. They must integrate AI across the organization and know when to draw on outside resources to reach AI maturity. Achievers are 32% more likely to derive value from their data than Experimenters to create custom machine learning apps or collaborate with a partner.

Designing AI considering its implications

Effective scaling of AI depends on creating ethically from the beginning. Organizations that can show superior, reliable technology solutions that are “regulatory ready” will have a substantial competitive edge in the market as AI regulation increases. Without it, firms risk losing the trust of their workers, consumers, and other businesses. Companies should develop risk management controls and accountability procedures to ensure that operations and services driven by AI are in line with the company’s fundamental values.

Businesses that do not significantly expand their AI spending risk falling behind. Leaders know that this is only the beginning of using AI to generate corporate value successfully. These high-achievers are committed to broadening AI applications while improving their solution integrations.

Tech firms with little legacy technology have a natural AI advantage. The majority of insurance businesses, however, are constrained by this history and subject to much more regulation. It should be no surprise that these industries have the highest and lowest levels of AI development. However, achievers exist in most industries, and all are anticipated to develop further.

However, even these “adults” will need to keep learning because technology changes every aspect of business, often necessitating a complete reinvention of the entire firm.

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Swapnil Mishra

Swapnil Mishra is a Business News Reporter with over six years of experience in journalism and mass communication. With an impressive track record in the industry, Swapnil has worked with different media outlets and has developed technical expertise in drafting content strategies, executive leadership, business strategy, industry insights, best practices, and thought leadership. Swapnil is a journalism graduate who has a keen eye for editorial detail and a strong sense of language skills. She brings her extensive knowledge of the industry to every article she writes, ensuring that her readers receive the most up-to-date and informative news possible. Swapnil's writing style is clear, concise, and engaging, making her articles accessible to readers of all levels of expertise. Her technical expertise, coupled with her eye for detail, ensures that she produces high-quality content that meets the needs of her readers. She calls herself a plant mom and wants to have her own jungle someday.

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