How AI Is Revolutionizing B2B Strategy

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.

Service operations are also witnessing a significant transformation, thanks to generative AI. The use of AI in customer care and back-office support is enhancing efficiency and improving the customer experience. AI-driven chatbots aren’t just good for sales; they also provide instant, intelligent responses to customer queries, elevating the level of service and support offered. 

If you need an example of how generative AI can easily enhance product offerings and service operations, look no further than Shopify. The ecommerce giant’s new AI assistant, Sidekick, is built using the ChatGPT API and helps customers use the site with more efficiency. 

How Leading Adopters Use AI in B2B

As someone who works in B2B SaaS, you’re likely not surprised by the industry trends and use cases for generative AI. Summarizing, analyzing, and creating documents—whether they be for sales, marketing, or customer support—is something your company has likely experimented with already. 

The real question is, what are companies doing to unlock the full revenue-boosting potential of AI?

According to the McKinsey report, most AI leaders aren’t just using generative AI to reduce costs but also to increase revenue in core business and create new revenue streams. These high-performing organizations are more than five times as likely to dedicate 20% or more of their digital budgets to AI compared to others. These companies are not just dabbling in AI; they are embedding it across at least four business functions, demonstrating a holistic and comprehensive approach to AI integration.

While most companies are concerned with using AI to reduce costs or take advantage of APIs to offer their own AI features, high-performing firms see more return on investment by taking a diversified approach. This is highlighted by two key usage differences: 

1. High-performing firms are nearly twice as likely to use AI to create new revenue streams
2. High-performing firms are much less likely to focus on cost reduction as a top objective

The second point is particularly important. While reducing costs through more efficient content creation or data analysis is important, it appears many companies are selling themselves short by focusing primarily on the abilities of tools like ChatGPT. 

How Companies Approach AI Risk Management 

Of course, it’s not all sunshine and rainbows in the AI B2B space. There are important risks to be aware of—not to mention ones that are likely to surface as the technology improves. While the early days of 2023 were filled with prophecies of global destruction, the focus has shifted to the practical dangers that AI poses to industry and society at large. 

Of the respondents from the McKinsey report, 56% cite the inaccuracy of generative AI as a relevant risk factor. This is followed closely by cybersecurity at 53%, as well as legal (46%) and regulatory (45%) risks. 

Interestingly, the actions these companies take don’t exactly align with stated fears—38% of companies are actively working to reduce cybersecurity risks, while only 32% are taking steps to address inaccuracy.

Now that you’ve got a better idea of how AI is shaping the B2B landscape, let’s take a look at the AI developers creating the models at the center of this revolution. 

The AI Developers Shaping the Future of B2B

There are lots of companies that can nominally claim to be influential in the AI space, but it’s the AI-model developers and tech giants who are truly shaping the future. OpenAI and its competitors are building a new digital infrastructure layer that can unlock new opportunities and enhance current capabilities.

According to Forbes, there are a handful of AI-model developers with the products, funding, research, and—most importantly—head start to truly shape the future of business and beyond: 

• OpenAI
• Anthropic
• Adept
• Inflection
• Cohere

We’ll close out this piece with a quick look at each company. 

OpenAI 

OpenAI is the central force in the AI industry, significantly impacting both B2C and B2B sectors with ChatGPT, Dall-E, and specialized enterprise ChatGPT models. The company also has a first-mover advantage, benefiting significantly from the massive amount of customer feedback and the model training it receives, particularly as usage rates skyrocketed over the last year.

No shocker here—OpenAI’s most influential contribution to the enterprise world is its ChatGPT model, which has been adopted by an impressive 80% of Fortune 500 companies and millions of individual users across the globe. The company recently released an “uncapped” Enterprise version of ChatGPT that removes usage limitations and offers a higher level of security. With a 32K token context window, the enterprise ChatGPT model can handle 4x the input of the consumer version, allowing for more extensive and continuous AI interactions.

OpenAI’s emergence onto the B2B AI scene has brought in a number of big names, including PwC, Square, Asana, Canva, Clearbit, and Riot Games. 

During its recent DevDay conference, OpenAI announced a slate of new releases that will further increase the AI developer’s importance in the B2B context. Companies can now apply the leading large language model (LLM) in a number of new ways:

• Assistants API—Gives developers the tools to create agent-like experiences within their applications 
• Code Interpreter and Retrieval—Reduces the complexity of building high-quality AI applications by handling many of the previously manual tasks
• Custom GPTs—Allows users to choose from a number of purpose-based GPT models or easily develop a custom version with simple instructions

While OpenAI has a sizable head start in terms of market presence, brand name, and user adoption, there are a number of competing model developers looking to stake out industry territory. 

Anthropic

Anthropic, an AI research and products company, is making significant strides in transforming AI in the B2B context. It’s raised over $1.3 billion in funding and is focused on AI safety, a topic that OpenAI has repeatedly come under fire for. Anthropic’s main offering, Claude, is an AI assistant that specializes in various areas such as customer service, legal, internal search, coaching, and sales, catering to a wide range of business needs.

Claude is available in two versions: 

• Claude Instant—A faster and more cost-effective model suitable for casual dialogue, text analysis, summarization, and document question-answering
• Claude—A more powerful version that excels in sophisticated dialogue, creative content generation, and detailed instruction-following

Anthropic has also formed a strategic partnership with Amazon. Claude is now generally available to all users of Amazon Bedrock, a service providing secure cloud access to foundation models and tools for building generative AI applications. This integration means that every Amazon Web Services (AWS) customer can now build with Anthropic and also has opportunities to customize and fine-tune Claude models. 

For a company that aims to dethrone OpenAI in the AI B2B segment, partnering with the largest cloud infrastructure provider in the game is a major step in the right direction. 

Adept

Adept comes in third on the model developer list. The company was founded in 2022 by an ex-OpenAI engineer and has already secured $415 million in funding. Like Anthropic, Adept is taking a more targeted approach to penetrating the AI B2B space. In this case, through a model that’s trained to manipulate other software tools. 

Adept’s ACT-1 uses the same underlying transformer technology as OpenAI. But instead of applying it generally to text manipulation, this model is trained specifically to navigate and use software tools through natural language. Routine tasks in key enterprise platforms that would typically involve numerous clicks, like adding a new lead in Salesforce or validating information in large CSVs, can be condensed into a single prompt for ACT-1.

Like all generative AIs based on LLMs, ACT-1’s ability to learn and improve from human feedback ensures that it becomes more efficient and tailored to specific enterprise needs over time. By bridging the gap between human language and digital execution, ACT-1 zeroes in on a lucrative segment of enterprise users. It’s still early days, but this decision could pay huge dividends down the road as Adept looks to dominate in B2B AI. 

Inflection

At first glance, Inflection AI seems like it’s directed more towards a consumer audience than an enterprise one. But with a top-notch leadership team, a major co-sign from Bill Gates, and one of the largest arsenals of computing power in the industry, this company is poised for massive growth in the AI industry. 

Inflection’s flagship product, Pi, is pitched as an emotionally intelligent personal assistant designed to cater to the unique needs of individual users. Unlike general-purpose AI models, Pi focuses on providing personalized assistance, offering empathetic, tailored interactions and productivity enhancements that can indirectly benefit enterprise environments.

In terms of funding and strategic positioning, Inflection has raised $1.3 billion—investors are clearly confident in the ability of this technology to scale. This funding is being used to build the world’s largest AI cluster, comprising 22,000 NVIDIA H100 Tensor Core GPUs. This technological infrastructure underpins Pi’s capabilities, enabling it to deliver sophisticated and responsive AI interactions.

While Inflection’s current focus is more of a B2C project, the underlying technology and the company’s strategic partnerships suggest a strong potential for future enterprise applications. The emphasis on personalization and emotional intelligence in AI could pave the way for more nuanced and effective AI tools in business contexts, potentially revolutionizing how enterprises interact with AI technology.

Cohere

Cohere is similar to Adept in that it’s seemingly skipping the consumer market and going straight to enterprise companies. The Toronto-based company has raised $435 million to develop a tool suite that enhances various aspects of business operations. Cohere’s enterprise knowledge assistant, Coral AI, is leading the charge on the enterprise front. 

Coral AI is tailored to augment the capabilities of different teams within an organization, from finance to customer support and sales. With over 100 integrations across CRMs, collaboration tools, databases, and more, this is the perfect example of an AI that engrains itself within the enterprise tech stack. This customization allows Coral to be more powerful and specific to the unique job functions of each team.

A key feature of Coral AI is its commitment to data security and privacy. The tool operates within the client’s secure cloud environment, whether through cloud partners like AWS, GCP, OCI, or virtual private clouds. Importantly, the data used by Coral stays within the client’s environment, ensuring that sensitive information remains secure and private.

The Cohere AI suite offers models and tools that can be broadly used across multiple business functions, including: 

• Text generation optimized for business and trained on practical use cases
• Software development in both English and multiple other languages
• Summarizing and searching large volumes of text in over 100 languages
• Classifying text for various applications like customer support routing and sentiment analysis 

Cohere is another example of a company that’s positioned perfectly to eat up real estate within B2B AI, skipping the bottom-up model for a more targeted approach to enterprise adoption. 

Get Ready—AI Is Transforming the B2B and B2C Landscapes

The landscape of B2B content creation is undergoing a monumental shift, propelled by the advancements in artificial intelligence and machine learning. As we’ve seen, generative AI is not just a fleeting trend; it’s fundamentally changing how businesses operate, innovate, and communicate. With AI-driven tools like ChatGPT, Jasper, and Anthropic’s Claude, companies are experiencing unprecedented improvements in efficiency, customer engagement, and innovation. These tools are reshaping marketing, sales, product development, and service operations, enabling businesses to interact with their customers more personally and effectively.

However, the integration of AI into B2B strategies is not without challenges. Companies must navigate risks such as AI inaccuracy, cybersecurity, legal, and regulatory issues. Despite these hurdles, the potential of AI to drive revenue growth and create new business opportunities is undeniable. As we move forward, it’s clear that AI will continue to be a critical driver of transformation in the B2B sector, offering a competitive edge to those who embrace its potential while responsibly managing its risks.

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