Artificial intelligence (AI) and machine learning are quickly becoming more than just buzzwords. These transformative forces are reshaping the very fabric of business operations.
Projections show that generative AI alone could add between $2.6-$4.4 trillion to the global economy—annually. According to some, that’s a conservative estimate.
Just like cloud computing transformed companies into “tech” companies, the integration of AI into these tech stacks means an increasing number of companies qualify as AI. Exploding Topics puts that number in the ballpark of 58,000.
Leading the charge in this AI revolution are a select few brands that stand out, poised to redefine the future of enterprise. From OpenAI, the pioneer that ignited the AI boom with groundbreaking tools like GPT-4 and Dall-E, to Anthropic with its specialized AI assistant, Claude, the AI B2B landscape is brimming with innovation.
In this post, we’ll explore how businesses have been implementing AI in the first boom year of this nascent technology, including:
- The industries, departments, and use cases driving adoption
- How leading adopters are strategically deploying AI for B2B growth
- Risks gaining the most attention from enterprise leadership
- How AI is being deployed successfully in the B2B context
- The companies driving change with enterprise AI solutions
We’ve got a lot to go through, so let’s get started.
How AI is Changing the B2B Landscape in Tech and Beyond
Earlier this year, McKinsey conducted a large-scale survey of enterprise AI adoption and usage for its state of AI in 2023 report. With responses from thousands of professionals across dozens of industries, it provides a great overview of the early impact generative AI is having in the B2B landscape.
The industries leading the adoption of generative AI will be a surprise to no one: Technology, media, and telecommunications companies are leading the way, with 33% of respondents from these industries using generative AI regularly at work and outside of work. The next highest tier of industries in terms of generative AI adoption in the B2B context includes financial, business, legal, and professional services at around 24% regular usage at and outside of work.
Regular workplace usage rates are bound to increase as companies adopt the systems, policies, and workflows to bring generative AI into the fold. Things may not change much from the outside, but let’s see how the leading adopters of AI use it to gain an edge in their industry.
How Leading Adopters Leverage AI in B2B
The explosion of generative AI onto the B2B scene is more than the markings of a chapter in tech; it’s a whole new novel. The technology is rapidly gaining traction across various business functions, with the McKinsey report finding that a third of companies now deploy generative AI in at least one business function.
Currently, the most prominent areas of generative AI application inside B2B enterprises are as follows:
- Marketing and sales (14%)
- Product/service development (13%)
- Service operations (10%)
Now, let’s look at the specific use cases where enterprise personnel are implementing generative AI to improve their performance and work.
Marketing and Sales
In marketing and sales, generative AI is revolutionizing how companies understand and interact with their customers. From vastly increasing the efficiency of written content creation to developing more personalized, customer-centric content, AI is enabling businesses to engage with their audiences with a new level of efficiency. The National Bureau of Economic Research estimates that new AI tools will increase productivity by between 14-34%.
Generative AI tools are leading the charge regarding the widespread application of artificial intelligence within the enterprise—particularly, tools like ChatGPT and Jasper. Text generation tools have created a whole new content creation workflow that companies are using to create marketing and sales assets more effectively.
Given that these tools are based on large language models trained on massive amounts of textual data, the most common marketing and sales use cases should come as no surprise:
- First-draft creation
- Document summary
- Personalized marketing
While these are relatively simple use cases, estimates put the revenue impact of generative AI on marketing at over $450 billion.
We already see major brands in the tech and media space taking advantage of AI for marketing and sales purposes. For instance, WIRED has a policy outlining how it uses AI in limited cases, like suggesting headlines and social content, while a number of companies are using chatbots powered by generative AIs to engage potential customers as soon as they reach a website.
As marketing and sales teams become more seasoned AI users, we’ll also see the implementation of AI for more complex marketing tactics like SEO management, automated content distribution, and dynamic content optimization.
Product Development and Service Operations
In product and service development, generative AI is not just streamlining processes; it’s fostering innovation. Companies are using AI to analyze customer data, extract new product ideas, design minimum-viable products, and even generate first drafts of technical documents. This makes sense, considering these use cases, like the ones from marketing and sales, are heavily reliant on the use of text. All this points towards an accelerated development cycle that helps brands launch new customer-centric products and services.
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