Technology that could increase a company’s profitability with an average of 38% by 2035 and provide an 80-fold cost reduction for call centers. This is exactly the assessment that global companies give to the influence of artificial intelligence (AI). Talking about areas with the successful implementation of AI and what kind of impact it provides – that’s today’s topic covered by Aleksandra Boguslavskaya, CEO of Data Science UA.
OpenAI’s ChatGPT made a disruption and brought AI to massive public attention, despite the fact that machine learning was widely commercially used during the last decade. No doubt, AI has become more accessible. Thanks to it, popularity has been growing, the number of investments has been increasing and technology has been evolving.
AI and LLM: where is the difference?
We call AI a big industry of creating machines that can do creative tasks like people do. It comprises many directions like text or video generation, object detection with computer vision, etc.
Large Language Model (LLM) is a type of AI that can understand human languages and generate text. ChatGPT is an accessible interface to an LLM.
Before concluding the current state of LLM’s role in business processes worldwide, let’s summarize the impact of LLM as technology in various business processes from 2021 onwards.
Impact on various sectors
Large Language Models (LLMs) like GPT-4 demonstrated a significant impact in various sectors:
- Customer Service and Support
Deployed for real-time support, they handle routine inquiries, enhancing customer service efficiency. - Technology and Software Development
They speed up software development, making coding more accessible through automation in code generation, debugging, and documenting. - Content Creation and Media
LLMs automate copy, report, and story creation, boosting efficiency in journalism, marketing, and entertainment. - Healthcare
They assist in patient triage, and medical information provisioning, and support clinical decision-making by analyzing medical data. - Legal and Compliance
LLMs streamline legal research, contract analysis, compliance, and parsing through documents to support legal processes. - Finance and Economics
In finance, they automate report generation, and risk assessment, and provide personalized investment advice while enhancing decision-making.
Generative LLMs are reshaping the global economy by automating tasks, boosting productivity, and fostering innovation across industries, though their ethical and social implications must be carefully managed. To dive deep into how this works, let’s just look at some examples.
LLM impact on the Customer Service and Support industry
Perhaps every B2C company has a customer support dept. According to many experts, this should have a positive impact on profits. Some numbers on generative AI impact are self-explanatory:
- Implementing AI in customer service can reduce costs by up to 30%. (VentureBeat)
- Successfully applying AI could increase a company’s profitability by an average of 38% by 2035. (Accenture)
- 3 in 4 companies that implemented AI saw new product sales increase by over 10%. (Capgemini)
- 66% of customer service professionals say AI has improved business performance by analyzing customer feedback. (Dialpad)
- AI-powered proactive chat can raise conversion rates by 15%. (Zowie)
- AI customer service can increase average order value (AOV) by as much as 47%. (Zowie)
- The average contact center conversation with a human costs $8. The average customer service interaction via chatbot costs 10 cents. (Gartner)
Speaking about what drives the costs down, it is important to understand customers’ needs.
Efficient service is critically important, as the vast majority of customers place it on par with the products the company offers, expecting immediate responses and seamless communication once they get in touch.
Delivering this level of service efficiency and engagement poses significant challenges for many companies, from staffing to ensuring consistent service experience. Moreover, most questions are similar, which makes AI integration easier but doesn’t reduce call center costs.
A notable percentage of service professionals indicate their departments, including service, sales, and marketing, utilize a shared CRM platform. This collaborative approach facilitates the deployment of automation and AI, markedly improving service efficiency, agent productivity, and customer satisfaction.
These are just a few of the different approaches typically done by companies mainly to cut costs and drive engagement.
Technology and Software Development
Talking about the shift from traditional development paradigms to AI-augmented approaches, we also discover positive economic impact.
For example, numbers in the white paper “Generative AI: Redefining the Economics of Software Development” by SoftServe say:
- Requirements management got a 44% productivity boost.
- Quality control improved by 62%.
- Architectural and tech design efficiency increased by 39%.
- Code and unit testing coverage rose by 42%.
- Deployment and release operations were 48% more efficient.
- Documenting product and technical specifications became 28% faster.
- Project management activities saw a 79% increase in productivity.
This generative AI integration led to an overall project completion time reduction of 31% and enabled teams to deliver up to 45% more output.
These were the key findings of the research, involving over 1000 SoftServe professionals across seven countries. The results are promising; they open the door to greater productivity, creativity, and efficiency at each stage of the software development lifecycle.
This approach, based on a balanced and informed implementation of Generative AI, improves not just efficiency but also the ability to handle more complex tasks and allocate time to value-added activities.
Content Creation and Media
According to McKinsey’s report, using LLM in marketing has a positive impact on growth for a company and for the economy in general. One of the most trending areas is media content generation and that was something we at Data Science UA have also noticed.
Generative AI could increase the productivity of marketing activities by 5-15% of total marketing spending. This does not account for the potential knock-on effects, such as higher-quality data insights. These could spur new marketing ideas and allow for a shift in resources toward producing higher-quality content for owned channels. And that, in turn, is potentially reducing the need for external channels and agencies.
Key insights of marketing upgrade
Efficient and Effective Content Creation:
LLM can drastically reduce the time needed for drafting content, ensuring uniform brand voice and style across different platforms. It facilitates enhanced personalization of marketing messages for different customer segments, depending on their measured behavior.
This adaptability could significantly boost customer value, attraction, conversion, and retention on a scale and efficiency unattainable through traditional methods.
Enhanced Use of Data
Identify trends, key market drivers, and opportunities, by interpreting and synthesizing information about your clients from texts, images, and other data structures. Working with all of this data is leading to more targeted customer profiles and channel recommendations.
Improved SEO
Through its ability to synthesize key SEO tokens and assist in digital content creation, generative AI can play a crucial role in optimizing marketing and sales components for search engines, leading to higher conversion rates and reduced costs.
Product Discovery and Search Personalization
Boost e-commerce by personalizing product discovery and search through multimodal inputs (text, images, speech) and a deep understanding of customer profiles. This can significantly improve website conversion rates by enabling more relevant product discoveries and generating personalized product descriptions. A great example is Amazon.
These advancements are poised to dramatically increase marketing efficiency and effectiveness, with a significant economic impact on overall productivity.
In general, LLM has a lot of potential integrations in every area. The numbers in the research demonstrate perspectives of using AI and the baby steps have been made by now. Companies that integrated AI already felt the economic impact.
