The natural starting point for AI implementation in B2B

Artificial intelligence (AI) has reached a critical inflection point. Some common questions at C-suite roundtables include “What is our AI strategy?” and “Where is the natural place to start?”  

Leading B2B companies are now reflecting on AI and assigning resources to execute for competitive advantage. 

This critical inflection point did not happen overnight, however. In fact, according to Gartner research¹, there were several breakthroughs over a 20-year span that contributed significantly to AI’s rise: 

  • 2010 – Natural-language modeling using vast amounts of data 
  • 2014 – Mastering context, or analyzing the language that surrounds specific words and phrases 
  • 2017-2022 – Implementing large language foundations that are fine-tuned over time 
  • 2022 – Accessing (and conversing with) a foundation at scale – the launch of chatbot ChatGPT 

While these breakthroughs were occurring, several other technologies reinforced AI’s position, including machine learning, the Internet of Things (IoT) and automation. A meaningful AI strategy includes all of these as part of an overall AI plan. Beyond technology though are real and important questions about humans and machines, and how companies balance risks and benefits to deliver optimal business value. 

Risks, benefits and culture shift 

In a 2023 Gartner¹ poll of 2,500 business executives, several benefits and risks were captured that are important to consider when evaluating AI: 

  • The risks of AI – accuracy, bias, legal (particularly IP and copyright), sustainability and security (particularly cybersecurity and fraud) 
  • The benefits of AI – customer experience/retention, revenue growth, cost optimization and business continuity 

The breadth of these risks and benefits necessitates multi-departmental, multi-year planning. Rather than starting with individual AI projects, the leadership team should consider how the organization’s intrinsic business value can be accelerated with AI capabilities.  

A similar umbrella concept for comparison is the digital transformation, where one-off projects were elevated to a broad portfolio of projects. And if your company isn’t even there yet, embarking on a digital transformation is the most natural place to start an AI journey. 

The natural AI starting point: Post-digital transformation 

When operations and commerce are digitized – the results of a digital transformation – the organization is ready for AI use cases. With a goal of improving efficiency, a company can begin to use AI by automating common repetitive tasks. 

According to Forrester analysts, a natural place for B2B companies to start is with Autonomous Workplace Assistants² (AWAs). AWAs are intelligent agents, or software robots that assist employees and automate business processes. These can be used in services like: 

  • IT Help Desk management (using software like Expressive) 
  • Service Worker recruitment (using software like Kristal) 
  • Virtual Sales Assistant support (using software like Drift) 

All these natural language processing (NLP) advances embed monitoring, conversation, detection and decisioning without the use of central orchestration³. In other words, the systems have enough knowledge to complete routine tasks, which frees up service professionals to tackle more complex problem solving. 

Beyond business process automation, another AI use case is product recommenders. Well-designed ecommerce systems can harness buying behaviors and large product data sets for smart suggestions, powered by AI. B2B buyers can be prompted to consider other complementary products or categories. 

With rich data and analysis of buying patterns, a smart system can suggest upsells at the point of sale, and before the anticipated need. In addition, a marketing system tied to these could extend AI, such as a promotional discount through email, that both times and recommends smart product add-ons when they’re most needed. 

Other natural AI use cases for digitally transformed companies are Visual and Voice Commerce⁴. AI can extend this trend through personalized recommendations or alternative buying sources based on image or voice match. Thanks to Siri, Alexa and Google Assistant this technology is becoming more ubiquitous in the market.  

Below is an example shopping experience where the buyer requests specific items to be placed in a cart, receives confirmation through visual and voice outputs, and places the order directly through the integrated Order Management System. Similarly in Conversational Commerce buyers can use bot technology for placing orders. 

In summary 

The world of AI is extensive and sometimes overwhelming. But understanding AI’s historical background, embracing the culture of AI, making digital transformation investments, and leveraging robust use cases can simplify the complex process and help B2B leaders to invest wisely. 



² Generative AI Owns The Top 10 Emerging Technologies In 2023 ( 

³ Eleven Top Autonomous Workplace Assistant Use Cases | Forrester 

‘Visual commerce’ — a sharp new focus on B2B ( 

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