Intro

Rob Garmaise, VP of AI research at Info-tech Research Group, is at the forefront of Info-tech research, helping clients identify best practices across their IT operations. They conduct extensive primary and secondary research, speaking with industry experts and other clients to understand the drivers of value and proof that a given practice leads to better results.

AI Vendors, Verticals, and Research Taxonomy

Rob explains that the firm has a vast research taxonomy, with AI being an important part of it. They have a team in place to connect with thought-leading vendors and their leading adopter clients to gather insights on various functions, rules, verticals, and sub-segments where AI is taking root. The strength in the marketplace currently lies in the horizontal focus on functions and roles across organizations rather than the various verticals or lines of business. Most AI vendors aim to maximize their total addressable market which is difficult to do when focusing on just one vertical.

The Market and Vertically-orientated Competitors

Rob predicts that the mix of vertically-oriented competitors will change as the market evolves. Currently, the strength is 80% on functions and roles, 20% on verticals. This approach allows AI vendors to maximize their total addressable market and stay competitive in the market.

In this discussion, Rob discusses the implementation of AI solutions in various functions and roles within companies, including IT. He highlights the strengths in CO generation, data and analytics, service management, HR, sales, and marketing.

AI in HR, Sales and Marketing, and Operations

In HR, AI is being used to improve employee experience by indexing content and interacting with users. Talent acquisition recruiting uses AI on both sides of the recruiting equation, with AI being  used in talent assessment, helping to cut through biases and improve diverse hiring. Sales enablement and sales automation tools are the top lead and revenue-driving categories, while customer experience is the top cost-saving category. Operations are also being explored, with AI parsing information captured from video cameras for various applications such as shop floor settings, retail environments, and restaurants. Natural language conversations with equipment can lead to predictive maintenance, allowing organizations to strategize and optimize operations. Robert goes on to explain more about the improvements made using AI in HR, IT, and sales and management.

AI-based Solutions in the Retail and Insurance Industry

The conversation turns to the use of AI in various industries, including retail, and insurance. In the retail industry, AI-based solutions have impressed with their ability to scan store shelves with smartphones and receive critical metrics like stock availability, pricing, promotion, and competitor positioning. Smart Digital Signage solutions can also be used to adapt to demographics and reactions of customers. In the insurance industry, AI-based solutions include smart digital signage that can adapt to demographics and react to customer reactions. In the insurance industry, AI-based solutions include smart digital signage that can adapt to different demographics and respond to customer needs. Companies are exploring AI solutions to improve employee experience, sales, and marketing, while also focusing on cost-saving and predictive maintenance strategies. Robert discusses the potential benefits of AI in retail, such as real-time reactions to client information, and automated stock out detection.

AI in the Legal and Financial Sectors

In the legal sector, AI is being used for various purposes, including legal research, contract review, and contract management. This is particularly important for law firms and organizations with understaffed legal teams. In manufacturing, AI is being used to offer real-time instructions to machine line operators. Rob talks about disappointments in areas like financial services, healthcare, and government. In financial services, AI is being used for fraud detection, digital trust, and remote inspections. In insurance, AI can parse frequent documents into well-constructed spreadsheets or databases, and can conduct remote inspections. Rob also points out areas of disappointment. 

Advice on Adopting AI 

The conversation turns to the trend of AI being bought rather than built, particularly in the context of AI models. AI should be bought unless a build is absolutely necessary. The build side involves more uncertain investment levels and lead times, as it can lead to app sprawl and uncertainty in the market. Companies are advised to be deliberate about their build decisions, especially when it comes to AI models. On the talent side, companies are hiring new types of Chief AI officers or existing employees, such as Chief Digital Officers, Chief Technology Officers, and Chief Information Officers. These individuals are often left in charge of driving AI forward, but they may not have the necessary skills for building a new and unique model. On the build side, companies may need additional data scientists and data modelers, which can be challenging to achieve. On the consulting side, there is a growing trend of companies using top strategy firms on multiple AI projects. While most clients are still trying to orient themselves, consulting firms can help direct them towards buy-side scenarios where a POC or two can be done without a large implementation. Rob also touches on the importance of understanding the market and the potential benefits of AI solutions.

Timestamps:

03:40: AI Market Insights and Research Methodology 

05:28: Practical AI Applications in IT and Service Management

06:53: AI in HR and Talent Management 

08:11: AI in Sales and Marketing 

09:43: AI in Operations and Predictive Maintenance 

11:31: AI in Retail and Supply Chain 

14:49: AI in Legal and Manufacturing 

17:55: Trends in AI Adoption and Talent Management

22:30: Consulting and AI Marketplace

Links:

Website: https://www.infotech.com/

YouTube: https://www.youtube.com/@InfoTechRG

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