The potential for AI to drive revenue and profit growth is enormous. It is key, however, that AI strategies are informed by a solid understanding of both the potential and risks of AI as well as the strengths and limitations of the underlying data fueling these programs
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Applying Past Lessons to Harness the Future Potential of AI.
Business leaders and investors universally agree that Artificial Intelligence (AI) and Machine Learning (ML) will transform their businesses by reducing costs, managing risks, streamlining operations, accelerating growth, and fueling innovation.
The potential for AI to drive revenue and profit growth is enormous. Marketing, customer service, and sales were identified as the top three functions where AI can realize its full potential according to a survey of 1,093 executives by Forbes.
· Sales organizations are dramatically improving sales performance by using algorithms to help with the basics of account and lead prioritization and qualification, recommending the content or sales action that will lead to success, and reallocating sales resources to the places they can have the most impact.
· Marketers are looking for AI to fuel enormous efficiencies by targeting and optimizing the impact of huge investments in media, content, products, and digital channels.
· And in customer service, AI is opening entire new frontiers in customer experience and success by applying NPL, sentiment analysis, automation, and personalization to customer relationship management. 90% of organizations are using AI to improve their customer journeys, revolutionize how they interact with customers and deliver them more compelling experiences.
To realize this potential to grow revenues, profits and firm value, businesses in every industry have announced AI focused initiatives. On average, investment in advanced analytics will exceed 11% of overall marketing budgets by 2022. Spending on AI software will top $125B by 2025 as organizations weave AI and Machine Learning tools into their business processes. In parallel, investors have poured more than $5 Billion into over 1,400 AI fueled sales and technology companies to meet this demand.
So far, the impact of these investments on growth and profits has not yet been transformational. Right now 70 % of AI initiatives are showing little or no return. And more businesses will struggle to realize the full potential of AI to grow firm value if their leaders don’t learn lessons from past transformations like the internet in the 1990s and cloud computing in the mid-2000s, according to Kartik Hosanagar, Professor of Technology, Digital Business and Marketing at the Wharton School and author of the influential book A Humans Guide to Machine Intelligence.
“What separates the AI projects that succeed from the ones that don’t often has more to do with the business strategies organizations follow when applying technologies than the ability of the technology itself to transform the business,” according to Professor Hosanagar. “Many of the problems are less about the tools and more about leadership. Most of the failures to harness the power of AI lies in human behavior, management understanding, and the failure to mesh algorithmic capabilities into organizations, business models and the culture of the business.”