Appendix

Generative AI by industries

The Infosys survey covers 12 sectors in the US and Canada, allowing us to compare how extensively and effectively each industry is using generative AI. Although most companies are investing in this technology — often heavily —there is a wide range of investment between sectors.

While differences exist between industries in the frequency of use cases that create value, only the retail and hospitality, and the logistics and supply chain sectors are statistically different from the others. These two sectors have significantly fewer respondents, which suggests these industry results are viewed more directionally.

Figure 10. Generative AI adoption and business value by industry

Source: Infosys Knowledge Institute

Automotive

Almost four in 10 (39%) of automotive respondents expect streamlined product development and design as highest positive impact for generative AI. This is almost twice the proportion of the overall survey (20%). At the same time, significantly fewer automotive respondents (15% compared to 26% overall) felt that increases in operational efficiency and automation will be the primary generative AI value areas.

Automotive: Expectations of most positive impact from generative AI

34% Enhance user experiences and personalization

39% Streamline product development and design

15% Increase operational efficiency and automation

11% Improve content generation and creativity

Appendix — Generative AI by industries

Generative AI Radar 2023: North America

Appendix — Generative AI by industries

Generative AI Radar 2023: North America

Potential use cases

Autonomous vehicles – Generative AI can be used to build virtual environments for training
User personalization – LLMs can be used to build in-car chatbot personal assistants. Generative AI can also predict driving routes, and personalize dashboards
Optimized marketing – Generative AI can develop personalized, customer-centric marketing content, and can be used to track marketing initiatives
Maintenance – Generative AI is being used to build predictive maintenance models and can be used to generate logs and advisory notices for drivers
Road freight – Generative AI can be used to train autonomous trucks, and to help plan the most effective and efficient delivery routes for goods

Consumer packaged goods

Overall, the largest group of respondents expect generative AI to have the biggest positive impact in enhancing user experiences and personalization. This sentiment was even stronger among respondents in the consumer packaged goods industry, with more than half (54%) feeling this way compared to 42% overall. Conversely, far fewer respondents from this industry (9%) felt generative AI would have the most positive impact on operational efficiency and automation compared to more than one quarter (26%) across industries.

CPG: Expectations of most positive impact from generative AI

54% Enhance user experiences and personalization

9% Increase operational efficiency and automation

22% Streamline product development and design

16% Improve content generation and creativity

Appendix — Generative AI by industries

Generative AI Radar 2023: North America

Potential use cases

Product descriptions – Generative AI can be used to create content that is personalized for individual consumers and optimized for SEO
Display design – Text-to-image tools can be used to generate marketing campaigns and packaging
Virtual shopping assistants – Generative AI can build 3D chatbots to help consumers choose products and guide them through the purchasing process
Inventory management – Generative AI can create logs and recommendations for stock management, comprising demand forecasting, allocation of stock and risk assessments
Visual merchandising – Generative AI can gather data from a store to track customer footfall and throughput to optimize store planograms

Energy, mining, and utilities

One in three respondents from the energy, mining, and utilities sectors expect enhanced user experiences and personalization to be the most important impact of generative AI. One in four respondents expects improved operational efficiency and automation to be the best. This sentiment is in line with our survey respondents overall. However, these sectors differ in the proportion of respondents that think the biggest impact of generative AI will come from streamlined product development and design. More than a quarter (29%) of respondents felt this is where generative AI would shine, compared to just 20% across all sectors.

Energy, mining and utilities: Expectations of most positive impact from generative AI

33% Enhance user experiences and personalization

29% Streamline product development and design

25% Increase operational efficiency and automation

12% Improve content generation and creativity

Appendix — Generative AI by industries

Generative AI Radar 2023: North America

Potential use cases

Grid management — Analyze data such as consumption patterns and load distribution to optimize grid performance and predict problems
Renewable energy — Help in the integration of renewable sources, including solar and wind, by predicting output and optimizing resource allocation
Demand forecasting — Enhance the accuracy of demand forecasts, allowing for efficient resource allocation and cost savings
Resource optimization — Simulate scenarios to optimize resource allocation
Ore quality prediction — Create models to predict the ore quality based on geological data
Impact modeling — Simulate the environmental impact of various mining methods

Retail and hospitality

Sentiments in retail and hospitality were similar to the survey overall. About the same proportion expected generative AI to excel in each of the four areas of potential benefit.

Retail and hospitality: Expectations of most positive impact from generative AI

43% Enhance user experiences and personalization

28% Streamline product development and design

20% Increase operational efficiency and automation

9% Improve content generation and creativity

Appendix — Generative AI by industries

Generative AI Radar 2023: North America

Potential use cases

Marketing – Large language models can draft highly personalized content for customers to boost engagement and conversion
Insights – Generative AI tools can process data and generate reports for marketers, helping them build more effective campaigns
Customer service/concierge services – Chatbots built on top of large language models can provide customer service ranging from help with orders and returns to booking rooms and tables, as well as assistance for visitors with local information and booking tickets for attractions
Translation – Generative AI can provide language translation services for overseas visitors

Healthcare and life sciences

Healthcare and life sciences respondents were much more likely to think generative AI would have its greatest positive impact on operational efficiency and automation. This was over 50% of life sciences and healthcare respondents compared to a survey average of just 26%. On the other hand, these respondents were much less likely to think that the biggest positive impact from generative AI would come from streamlined product development and design or improved content generation. Only about 1 in 20 respondents from this sector felt these were the areas that generative AI would do best. This is compared to 20% of all respondents for streamlining product development and 13% for content generation.

Healthcare and life sciences: Expectations of most positive impact from generative AI

35% Enhance user experiences and personalization

5% Streamline product development and design

54% Increase operational efficiency and automation

6% Improve content generation and creativity

Appendix — Generative AI by industries

Generative AI Radar 2023: North America

Potential use cases

Drug, gene, and protein sequence design — Accelerate drug discovery by designing molecules and proteins with specific properties and optimize synthetic gene design for biomanufacturing
Personalized treatment plans — Analyze a patient's medical history and other factors to generate customized treatment plans
Enhanced medical imaging — Use AI algorithms to improve the accuracy of medical imaging techniques like computerized tomography and magnetic resonance imaging scans by automatically identifying abnormalities
Patient triage – Chatbots based on specialized large language models can provide first-line patient triage, assessing symptoms, providing reassurance and sending the patient to an appropriate human professional

High tech

High-tech respondents differed little in their opinions on user experience and product development. However, they were the most likely to think that generative AI’s biggest positive impact would be increased efficiency and automation (34%). The overall average was 26%. They were also the least likely to rank improved content generation and creativity as offering the biggest positive impact (5%), compared to 13% overall.

High tech: Expectations of most positive impact from generative AI

43% Enhance user experiences and personalization

18% Streamline product development and design

34% Increase operational efficiency and automation

5% Improve content generation and creativity

Appendix — Generative AI by industries

Generative AI Radar 2023: North America

Potential use cases

Data analytics – Generative AI can be used to generate reports from data analysis to highlight narrative points for storytelling and to flag up anomalies and problems
Software creation – Tools such as Microsoft’s Copilot are being used to generate code, as well as review existing code, and to act as an assistant for software developers
Software analysis – Generative AI can analyze completed code to identify bugs and suggest fixes. It can also analyze code for adherence to coding guidelines, ensuring consistency across the whole codebase
Business analysis – Generative AI can review code to create reports to be used by the wider organization, including business analysts and product managers

Insurance and financial services

Respondents from the insurance and financial services industries are generally in line with the survey average for where generative AI will have its greatest positive impact — except in one area. Almost one quarter (23%) of insurance and financial services respondents expect that generative AI will be most impactful in improving content generation and creativity. This is significantly higher than the survey average of 13%.

Insurance and financial services: Expectations of most positive impact from generative AI

36% Enhance user experiences and personalization

20% Streamline product development and design

21% Increase operational efficiency and automation

23% Improve content generation and creativity

Appendix — Generative AI by industries

Generative AI Radar 2023: North America

Potential use cases

Document management – Similarly, large language models trained on the firm’s corpus can provide document summaries
Fraud detection – Generative AI can identify anomalies and generate reports flagging potential fraud
Customer service – Chatbots built on large language models trained on domain-specific data can manage interactions with customers from loan decisions to helping report issues
Training – Generative AI tools can be used to create firm-specific and role-specific training materials, from videos to interactive scenarios and role-play
Employee compliance – Generative AI can create listening tools that monitor email, voice telephony and messaging across a firm to spot any issues with compliance and reporting

Telecommunications

Telecommunications respondents provided similar answers to the overall average, except in one area. Significantly fewer (11%) expected the most positive impact from generative AI to come from operational efficiency and automation. This is about half the proportion of the survey average of 26%.

The telecom sector is already rolling out generative AI for customer interactions. In Australia, Google’s Dialogflow is being used by Optus, one of the largest telcos in the country, to power virtual agents for customer support. This technology comes with prebuilt agents, which can be rolled out quickly to deal with queries about bill payments and orders without requiring custom programming.

Telecoms: Expectations of most positive impact from generative AI

52% Enhance user experiences and personalization

16% Streamline product development and design

11% Increase operational efficiency and automation

21% Improve content generation and creativity

Appendix — Generative AI by industries

Generative AI Radar 2023: North America

Potential use cases

Customer support – Chatbots built on large language models and trained on telco-specific data can help users with billing queries and orders
Streamlining operations – Generative AI tools can speed up diagnostics and analysis, and help manage deployment of resources to repair and upgrade installations
Engineer support – Generative AI can be trained on the network topology and guide engineers through a task by providing interactive guidance rather than relying on the human learning myriad manuals
Network optimization – Generative AI can analyze network data and conditions and generate insights to streamline deployment of resources for maintenance and repair

Logistics and supply chain management

Sentiments in logistics and supply chain management were similar to those of consumer packaged goods. Many more respondents in this industry (66%) expect generative AI to excel at enhancing user experiences and personalization, compared to 42% overall. Further, just 3% of logistics and supply chain respondents expect generative AI to make product development and design more streamlined, a fraction of the 20% across sectors.

Logistics and supply chain management: Expectations of most positive impact from generative AI

66% Enhance user experiences and personalization

3% Streamline product development and design

16% Increase operational efficiency and automation

15% Improve content generation and creativity

Appendix — Generative AI by industries

Generative AI Radar 2023: North America

Potential use cases

Route optimization – Generative AI can assess and suggest the most efficient routes for delivery runs based on data such as road conditions, weather and driver availability
Risk management – Generative AI can analyze data on geopolitical concerns, weather, industrial unrest and more to produce dashboards where workers can see issues at a glance, and can generate reports to suggest mitigations
Supplier management – Chatbots built on large language models can facilitate interactions with suppliers and pull insights from data to build into interactions with suppliers. Additionally, they can pull in data from external sources such as news articles to refine understanding of trends that might impact suppliers

21% Increase operational efficiency and automation

Manufacturing

Sentiments in manufacturing were similar to those of the survey as a whole. About the same proportion expected generative AI to shine in each of the four areas we asked about when looking at responses across industries.

Manufacturing: Expectations of most positive impact from generative AI

42% Enhance user experiences and personalization

28% Streamline product development and design

9% Improve content generation and creativity

Appendix — Generative AI by industries

Generative AI Radar 2023: North America

Potential use cases

Product design – Generative AI can be used to accelerate the design both of entire products, and of components
Maintenance – Generative AI tools can be used to monitor machinery failures and predict potential breakdowns, enabling proactive management of equipment
Quality management – Training an AI on images of similar products and identifying those that were defective can help predict potential problems with a new product
Inventory management – Generative AI can simulate scenarios such as weather-driven surges in demand and use historical data to fine-tune production schedules and optimize stock levels
Cost management – Using generative AI tools to manage design, maintenance, and risk can reduce costs of production substantially