AI Disclosure Trends: How companies are adopting AI and what they’re saying about it
With the explosion of artificial intelligence (AI) tools like ChatGPT- the viral chatbot that generates conversational responses to written inputs from users- has made AI the latest buzzword. So it’s no surprise that analysts and investors are increasingly interested in understanding how companies integrate these solutions within their business models, also the resulting impact.
94% of business leaders agree that AI will be critical to the success of their companies over the next five years, according to Deloitte’s latest “State of AI in the Enterprise” survey. And while the implications of adopting AI across industries varies, we’re seeing commonalities in medium and long-term goals when it comes to integrating this new technology. InspIR identified the following trends when we analyzed quarterly results commentary, investor days, and other financial community interactions and publications:
- Improve efficiency: Companies that are integrating AI solutions internally highlight how these tools will help enhance efficiency. They expect to reduce operational costs and minimize human error by automating certain routine labor-intensive manual processes; AI tools can therefore automate repetitive tasks, enabling a focus on more important aspects of work.
- Attract new customers: By analyzing consumer behaviors, companies are also developing new technologies to help identify and gain new consumers. Additionally, some companies emphasize how they’re designing new products and services to meet specific customer demands. The retail industry is leveraging AI to analyze data- including past purchases, customer preferences, and demographics- to offer personalized product recommendations and marketing messages that are tailored to individual customers. This not only helps to increase customer engagement but also works to produce higher conversion rates. To give an example, the rise in the use of chatbots and virtual assistants powered by AI and ML have enabled retailers to offer 24/7 customer support that would have otherwise been limited to their normal business hours. Harvard Business Review also shared a piece in April discussing AI as the common thread for successful firms ability to predict customer behavior.
- Strengthen cybersecurity protocols: Data protection is another important reason for adopting AI solutions. Companies are increasing headcounts to develop their own protocols to address cybersecurity threats, protect their data, and manage risk. Generative AI models can be used to significantly enhance the scanning and filtering of security vulnerabilities, according to a Cloud Security Alliance (CSA) report released in April exploring the cybersecurity implications of LLMs.
- Elevate the customer experience: AI can also add value externally by improving customer service. Companies are creating new functionalities that enable consumers to save time and have a more personalized experience; integrating AI to find products and services more quickly, receive tailored recommendations, and obtain real-time support through online chat functions. Advanced AI also makes it possible to improve accuracy in ways simply not feasible with manual processes. For example, when a questionable transaction is initiated, the AI system can reach out to the customer to confirm the transaction through a trusted device such as a cell phone. This kind of real-time communication not only improves fraud detection, it increases customer confidence.
- Monitor competitors: Processing and analyzing competitor data is another element to consider. Companies can better understand the performance of their competitors to gain a competitive advantage. There’s a tremendous amount of competitor data in the public domain but it’s often dispersed and opaque. AI-enabled competitive intelligence can help companies gather it, sort it and draw insights from it. New AI and machine learning techniques can streamline and accelerate this lengthy task. SaaS platforms use AI to track and collect historical and real-time data insights, which allows businesses to use information culled from competitors’ digital footprints.
- Optimize processes with suppliers: Companies are implementing AI solutions to optimize processes with suppliers and external stakeholders, such as intelligent onboarding processes or other protocols that allow suppliers to operate with the business in a more efficient and seamless way. Generative AI models can also be used to address supply chain security risks by identifying potential vulnerabilities of vendors.
- Track performance, including ESG: There is no better tool than AI to monitor and track financial performance and sustainability metrics such as carbon emissions, water and electricity consumption, and others. AI can also provide data-driven recommendations in these areas.
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