AI for Profit: How Generative AI is Reshaping Revenue Strategies

Introduction

In the ever-evolving landscape of enterprise technology, companies are not just adapting to changes; they are proactively seizing opportunities for business expansion and monetization. Generative AI is a prominent example of this ongoing trend. This technology has witnessed an adoption rate that surpasses even some of the most transformative innovations of recent times, including RPA and IoT. This is because generative AI represents a significant shift in how enterprises approach problem-solving, content generation, and customer interactions. Unlike previous technologies, which often required significant customization and integration efforts, generative AI platforms have become increasingly user-friendly and versatile. This surge in enthusiasm among businesses to embrace generative AI raises important questions about the practical implications of this newfound obsession.

One of the practical implications of the generative AI boom is the potential for substantial productivity gains. This has led to its seamless integration into various departments, including marketing, operations, and IT, yielding substantial improvements in productivity, expedited processes, and better alignment with user needs and expectations. For instance, Vodafone reported its developers’ productivity increased 30%–45% in trials that involved about 250 developers. Similarly, the United States Steel Corporation anticipates a reduction of around 20% in the time needed to complete a work order by using MineMind™, a proprietary generative AI application for equipment maintenance.

But the benefits of generative AI go beyond productivity improvements. Generative AI can also open doors to new monetization opportunities. By strategically leveraging this technology, companies can tap into its potential to increase revenue streams and profitability.

Monetization opportunities

The COVID-19 pandemic marked a pivotal moment for organizations, urging them to shift from traditional customer engagement practices to digital touchpoints. Generative AI is becoming a transformative tool in this shift, setting a new standard for customer delight through hyperpersonalization. While the direct financial impacts of generative AI might not be glaringly evident, its role in enhancing customer interactions is crucial for building loyalty and retention, which will contribute significantly to long-term revenue growth. By prioritizing customer experience and using generative AI for tailored interactions, organizations are laying the groundwork for sustained revenue growth and a strong competitive position. The following enterprise examples testify to the strategic value of integrating generative AI into customer experience initiatives.

1. Crocs, Max Life, and Thomas Cook achieved up to a 20% increase in customer engagement through a marketing solution called Netcore Gen AI™, which enhanced content personalization, visual product discovery, and streamlined cross-channel campaigns.
2. Instacart integrated a ChatGPT-powered search bar on its platform, offering personalized interactions based on users’ past shopping activities. This feature opens a new revenue stream, as brands can now pay to sponsor their products, ensuring top placement in search results, similar to Google’s search advertising model.
   

   Figure 1: Generative AI projects distribution based on business objectives

While most enterprises, around 90%, are content with using generative AI to boost operational efficiency, a small yet innovative segment of companies recognize its broader potential, as shown in Figure 1. These pioneers understand that generative AI’s benefits extend beyond mere process improvements. Currently, the focus for most businesses is on proving the technology’s value in their operational workflows. However, in 2024, it is poised to witness a substantial transition, as companies aim to scale their generative AI trials, moving past just productivity and efficiency gains toward establishing distinct market positions. As monetization-focused initiatives accelerate, three types of business models are beginning to emerge:

Proprietary, large language model-backed services: These businesses strive to carve out distinctive business models, transitioning from using generic large language models (LLMs) to creating proprietary ones. They are tapping into their extensive internal datasets to unveil novel revenue streams through innovative services and customer experiences. This model is currently in the pre-monetization stage.

• • Moody’s: Established a strategic alliance with Google Cloud to create tailored LLMs specifically designed for finance professionals to conduct in-depth analyses of financial statements, disclosures, and related content more efficiently. Moody’s will leverage its extensive experience in financial data and reporting to enable clients to directly query and extract actionable insights from financial documents.
  • Bloomberg: Launched a proprietary, 50-billion parameter LLM for the finance sector to assist clients in sentiment analysis, named entity recognition, and news classification. It plans to integrate this model into the features delivered through its terminal software. To enhance the model’s performance and accuracy in financial tasks, Bloomberg integrated over 100 billion words from FinPile, a proprietary dataset encompassing two decades of financial information.

New product features as a service: This model is predominantly prevalent among high-tech companies known for their willingness to embrace risk and their understanding that innovation is essential to remain competitive in a rapidly evolving technological environment. These companies have more quickly derived financial gains from generative AI than their counterparts in other industries.

• • Blast Motion has traditionally provided athletes, specifically baseball players, with detailed charts and time-series data capturing aspects like rotation, acceleration, and swing. They are taking a significant leap forward with generative AI, providing real-time recommendations on swing techniques by comparing a player’s swing against an ideal benchmark. For instance, if a change is detected in a player’s contact angle during a run, it is flagged. Moreover, analyzing data over weeks allows the system to spot subtle shifts in a player’s technique based on which personalized training is offered. Blast Motion provides this generative AI-driven feedback as a premium subscription service.
  • In May 2023, Adobe launched its Firefly services to generate images, apply virtual effects, and create new fonts based on text prompts across 100 languages. Its Q3 2023 earnings surpassed Wall Street predictions, owing to its strategic move to incorporate generative AI into its product suite for document processing and photo and video editing over the past six months. Starting November 2023, Adobe plans to implement premium pricing for its products, anticipating a revenue surge in the subsequent quarters.

Expansion into an untapped client base

• • CareCloud has partnered with Google Cloud to enhance the operational efficiency of ambulatory healthcare practices using generative AI. They are focusing on around 48,000 outpatient clinics in the US to equip doctors and clinicians with patient data analysis, enabling them to build comprehensive care plans. These care plans encompass medications, lab orders, diagnoses, and procedures based on the patient’s clinical history and current symptoms. Access to this data was traditionally limited to large hospitals.
  • HDFC ERGO established a generative AI CoE with Google Cloud to offer hyperpersonalized customer experiences using generative AI. They have explored alternative channels for communication, especially for sectors like agricultural insurance, where the traditional question-and-answer approach is unsuitable. To connect with farmers effectively, HDFC ERGO integrated NLP and introduced voice functionality on WhatsApp. This allows farmers to ask questions and receive responses via voice messages, enhancing accessibility and engagement.

Industries at the forefront of revenue-impacting projects

Figure 2: Distribution of generative AI projects across industries based on business objectives

1. High-tech and telecom

As mentioned, the high-tech sector has taken a proactive approach to embracing generative AI for monetization. This includes introducing subscription-based services for unique content generation and intuitive knowledge search. Some companies have gone even further, utilizing their tools and platforms to explore and expand into new industry segments.

• • In October 2023, LexisNexis launched Lexis+ AI, a generative AI platform, enabling advanced features such as conversational search, intelligent legal drafting, insightful summarization, and document upload capabilities.
  • South Korean firm Wayne Hill, an AI video tools provider, ventures into movie production with generative AI, including science-fiction films and diverse content such as music videos and digital twins.

Telecom companies are providing region-specific, private LLMs to enable enterprises to develop generative AI applications around areas such as knowledge management and document processing. They are also building industry-specific, multilingual LLMs to support generative AI integration projects for network operators.

• • KT group launched a new generative AI service comprising a suite of private LLMs ranging from seven billion to 200 billion parameters. This service enables local B2B firms to build generative AI applications across sectors such as financial services, manufacturing, and public services.
  • SK Telecom and Deutsche Telekom are building an LLM, pre-trained on telecom data. This LLM will assist network operators across Europe, Asia, and the Middle East in integrating generative AI capabilities into customer services.

2. Travel and transportation

Travel companies have started using generative AI to create personalized travel itineraries and offer round-the-clock travel bot assistance at a premium fee. On the other hand, logistics companies are tapping into their extensive transportation data repositories to introduce new service solutions backed by generative AI capabilities.

• • Uber Freight launched its Insights AI solution, which leverages generative AI to assist shipping companies in analyzing travel routes and optimizing their operations.
  • Skyscanner launched a new generative AI platform to assist users with travel planning and personalized itinerary creation.

3. Banking and financial services

In the banking and financial services sector, generative AI is pivotal in creating synthetic datasets to strengthen various areas such as fraud detection, money laundering prevention, risk assessment, and credit scoring. These applications result in substantial cost savings by preemptively identifying and mitigating risks. Moreover, the sector harnesses generative AI to craft tailored solutions such as personalized financial planning and advisory services, elevating the customer experience by 15%–20%. Additionally, generative AI aids in constructing a comprehensive, subscription-based database encompassing social media, ESG, web usage, and online transaction data, which can be offered in a data marketplace to private equity firms and the telecom sector.

• • One Zero Digital Bank partnered with AI21 Labs to launch a generative AI-powered conversational AI assistant. Through this AI assistant, it aims to extend its private banking services to a large segment of customers, which is currently limited to only a few clients due to a lack of employee bandwidth.
  • Pentagon Credit Union is using generative AI to expand its customer interaction channels and add a dedicated personal assistant that can provide customers with hyperpersonalized marketing campaigns and upsell and cross-sell other financial products and services based on their preferences.

4. Media and entertainment

With the US streaming-subscription churn rate standing at a concerning 37%, as reported by Deloitte, the media and entertainment industry is proactively turning to generative AI. They harness this technology to develop subscriber relationships, aiming to establish a stable, long-term connection. They are expediting content creation that resonates with diverse audiences and markets, aided by text-to-video tools powered by generative AI. They also use generative AI to analyze customer content consumption patterns, tailoring subscription plans with localized, genre-specific, or language-specific content. Furthermore, they utilize generative AI to generate personalized advertisements, boosting user engagement by aligning with individual interests and preferences.

• • Spotify launched a generative AI-powered music curation tool that provides personalized music recommendations based on listening habits. It also plans to leverage generative AI to create short narrations of audiobooks to increase customer engagement.
  • Spinnin’ Records, a subsidiary of Warner Media Group that focuses on electronic dance music, partnered with Endel, a generative AI startup, to create 50 new albums focused on mental health and relaxation. Through this partnership, it plans to expand its market reach across the functional music segment.

5. Retail and CPG

A retail security survey performed in 2022 by the National Retail Federation revealed retail inventory loss is at about USD 100 billion, prompting the industry to use generative AI for enhanced analytics. By analyzing a customer’s preferences in real time, generative AI is helping retailers in upselling and cross-selling opportunities. This sector also leverages generative AI to drive profitability through predictive strategies, enabling agile planning cycles even in challenging economic conditions. Similarly, some companies are also building proprietary LLMs to assist customers in using generative AI across activities such as marketing, customer experience, and supply chain optimization.

• • JD.com launched its 100 billion parameter LLM to facilitate Chinese companies to create generative AI applications such as telemedicine and marketing campaigns across sectors such as retail, logistics, financial services, and healthcare.
  • Seven-Eleven Japan uses generative AI to optimize its product planning process by analyzing consumer consumption preferences and market trends. Through this approach, it plans to expand its proprietary product portfolio across its 9,000 retail stores.

6. Healthcare providers

In the era of value-based care, healthcare providers grapple with the imperative of meeting financial incentives while tackling challenges such as controlling healthcare costs, reducing health disparities by race and ethnicity, and ensuring the delivery of quality care through personalized treatments. Generative AI emerges as a valuable tool, assisting providers in crafting low-cost, hyperpersonalized care plans to effectively meet their objectives.

• • Hackensack Meridian Health partnered with Google Cloud to offer generative AI capabilities to caregivers through its cloud data management platform. This platform will assist doctors with personalized health plans and recommendations.
  • UnitedHealth has rolled out a virtual assistant with generative AI capabilities, featuring a chatbot that gathers patient data. This initiative aims to establish a comprehensive, 360-degree view of customer profiles, facilitating the development of personalized healthcare programs and elevating customer satisfaction.

The Way Forward

Figure 3: The 3-P approach for monetizing business with generative AI

Policy: To harness the potential of generative AI for monetization, establish a strategic policy. Begin with full-stack observability for application environment understanding and chart a road map for integration. Establish AI-first value chains and identify potential monetization avenues. However, adopt a practical approach by initiating small-scale experiments before delving into client-facing revenue opportunities. Lay a solid foundation by implementing best practices for data management (data lineage, integration, quality, and validation) and workflow management in a hybrid cloud environment. Managing risks will be pivotal, so involve legal teams in project approval to ensure compliance and mitigation of potential issues. Establish a responsible AI framework to ensure the ethical and secure utilization of generative AI within a controlled environment. This multifaceted policy will empower enterprises to effectively harness generative AI for monetization.

Marqeta prioritizes generative AI in its road map. It invested in an internal code generation tool that streamlines coding and testing tasks by up to 75%. It now aims to capitalize on the AI opportunity by venturing into external client services. In August 2023, it launched Marqeta Docs AI, an AI-powered Q&A tool to deliver a higher customer experience.

People: Empowering innovation at the grassroots level through hackathons will ignite creativity and engagement, enabling employees to actively contribute innovative ideas to advance generative AI. Simultaneously, appointing an AI chief officer is pivotal for steering the strategic vision and effective implementation of AI initiatives. As technology transforms job roles, leaders should proactively plan and offer employees opportunities for reskilling and upskilling to adapt and thrive in an evolving landscape. These combined actions will establish an organizational culture that emphasizes the human element from the outset.

Disney is establishing an 11-member team comprising experts in AI and ML to assess the potential applications of traditional and generative AI within various business divisions, including studios, theme parks, and advertising, and build in-house AI applications.

Partnerships – To fully capitalize on AI endeavors necessitates the establishment of a robust partner ecosystem involving consultants, platforms, and service providers. Consultants play a pivotal role in identifying high-ROI use cases, devising strategic road maps, and managing technology-related risks. Digitally-mature enterprises often collaborate directly with generative AI platform providers, especially hyperscalers, because of their existing, long-term relationships. Conversely, some organizations opt for service providers to navigate integration and change management, leveraging their technology and domain expertise for a smoother transition.

NatWest is expanding its partnership with AWS to integrate generative AI into its business processes. In this collaboration, its data scientists and engineers will work with specialist teams at the AWS Generative AI Innovation Center, launched in June 2023 with a significant USD 100 million investment. Together, they will cocreate AI products using Amazon Bedrock’s foundational models.

By Chandrika Dutt, Research Leader, Avasant and Abhisekh Satapathy, Senior Analyst, Avasant