Source URL: https://slashdot.org/story/25/10/09/1132230/mckinsey-wonders-how-to-sell-ai-apps-with-no-measurable-benefits?utm_source=rss1.0mainlinkanon&utm_medium=feed
Source: Slashdot
Title: McKinsey Wonders How To Sell AI Apps With No Measurable Benefits
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AI Summary and Description: Yes
Summary: The text discusses the challenges faced by software vendors in monetizing AI effectively, as highlighted by a McKinsey & Company report. It emphasizes issues like inflated costs, the struggle to demonstrate ROI, and problems with scaling adoption and pricing models after AI integration. This insight is crucial for professionals in the fields of AI, cloud, and infrastructure security to understand the economic implications of AI deployment.
Detailed Description:
The analysis of the McKinsey & Company report highlights several key challenges software vendors encounter when incorporating AI into their products. These issues have significant implications across various sectors, particularly in relation to the economic aspects of AI adoption in the cloud and software security environments.
– **Inflated Costs for Customers**:
– Many vendors present AI as a means to cut costs by reducing the workforce. However, reports show that this is not currently happening; instead, costs are rising due to the implementation of AI.
– An HR executive from a Fortune 100 company has noted that deploying AI tools, such as “copilots,” has not led to decreased headcount as expected.
– **Demonstrating ROI**:
– Only 30% of software firms have managed to provide quantifiable returns on investment from AI deployments, raising concerns among customers about the real savings and effectiveness of AI initiatives.
– The substantial investment in developing sophisticated AI models contributes to increased overall costs for customers without guaranteed savings.
– **Challenges in Scaling Adoption**:
– The report highlights the necessity for extensive change management efforts to ensure successful adoption of AI capabilities in business operations.
– A recommendation is made that for every dollar spent on AI model development, an estimated three dollars should be allocated to change management activities, including user training and ongoing performance monitoring.
– **Complicated and Unpredictable Pricing Models**:
– A significant barrier to customer satisfaction stems from unclear pricing structures related to AI capabilities, making it difficult for customers to anticipate how costs will increase based on their usage.
– These complexities deter potential customers and create uncertainty in budgeting for AI investments.
In conclusion, as professionals in AI, cloud, and infrastructure fields assess the report’s insights, they should consider these economic challenges when planning AI integration. Understanding financial implications, ensuring proper investment in change management, and developing transparent pricing models are paramount for driving successful AI adoption and achieving long-term value within their organizations.