August Insights: Discover GenAI case studies, strategies and address challenges

Welcome to the August Edition of Calls9 Newsletter!

As generative AI adoption grows, businesses are presented with exciting opportunities but also complex decisions. Whether you're contemplating how to integrate GenAI into your operations, examining how global industry leaders are leveraging GenAI to revolutionise customer experiences, or grappling with the challenges of AI accuracy, this edition has been crafted with you in mind.

How global leaders use GenAI agents to enhance customer experience

Explore how nine top brands, such as Klarna, ING Bank, Heathrow Airport, H&M, Mercedes-Benz, and more, are setting new standards in customer service with Generative AI. These AI agents are not just automating routine tasks—they’re personalising customer interactions on a massive scale, delivering efficiency and satisfaction like never before.

• Increased satisfaction and profitability: Klarna's generative AI agent manages 75% of Klarna's customer service interactions—approximately 2.3 million conversations—achieving satisfaction scores comparable to those of human agents. Moreover, the agent's efficiency can potentially increase Klarna's profits by $40 million annually.
• Personalisation at scale: IHG Hotels & Resorts' GenAI-powered travel planner assists guests in planning their trips by offering personalised recommendations for over 6,000 hotels worldwide.
• Increased efficiency: H&M's GenAI-powered shopping Assistant has reduced response times by 70% compared to human agents and offers a voice search feature in the mobile app.

Access the full article

The inaccuracy challenge: Can you really trust generative AI?

As powerful as Generative AI is, its accuracy remains a significant concern. This article addresses the risks—such as the "black box" problem, hallucinations, and inherent biases—and provides strategies to mitigate these issues, ensuring your AI initiatives are both effective and ethical.

• Top GenAI Challenge in 2024: In a 2024 McKinsey survey, 63% of respondents flagged inaccuracy as the biggest risk with generative AI, up 7% from 2023.
• Root Causes of Inaccuracy: Generative AI inaccuracies stem from its opaque "black box" nature, the tendency for AI hallucinations, and biases embedded in the training data.
• Mitigation Strategies: Enhance AI accuracy by leveraging high-quality, diverse data, integrating Human-in-the-Loop processes, opting for Private AI platforms over public tools, and ensuring continuous model training and real-time monitoring.

Access the full article

Generative AI applications: Build, Buy, or Partner?

Are you considering incorporating Generative AI into your business? This article navigates the critical decision-making process of building a custom generative AI application in-house, buying an off-the-shelf product, or partnering with an expert AI agency. We dissect the pros and cons of each approach and provide a detailed comparison table to help you align your generative AI strategy with your unique business goals.

• Build: Full control and customisation for complex needs, but costly and time-consuming.
• Buy: Quick, cost-efficient deployment with less customisation; ideal for standard solutions.
• Partner: Combines expertise and customisation, perfect for tailored strategies without internal overhead.

Access the full article

Supercharge your strategy - Download our exclusive GenAI resources

Don't miss out on our exclusive generative AI resources, designed to guide business leaders through every step of GenAI adoption. Our comprehensive toolkit includes a 70+ page GenAI guide, an editable business case template, and an interactive checklist—everything you need to integrate GenAI into your operations successfully!

• The Ultimate GenAI Guide
• GenAI Implementation Checklist
• Generative AI Business Case Template