LLMs, including those powering ChatGPT, are refining the rules of marketing by mastering human language intricacies and offering fine-tuning capabilities. Once trained with large amounts of data (text, images, or audio), these models can be adapted and optimized for a variety of tasks. As a result, they can be reused or repurposed in a multitude of ways. Accenture's research2) highlights the transformative potential, with 65% of worker time in language-related tasks being potentially enhanced through LLMs, promising improved customer experiences and streamlined marketing efforts. Imagine the potential of getting code written, images created from text and in a contextual setting or videos produced form textual descriptions: true value emerges when customization becomes the norm, aligning these technologies with your unique marketing strategies.

There is a plethora of applications for increased effectiveness in marketing and digital commerce, among others:

• The most extensive use today is to perform search and data extraction. Companies can use GenAI, especially LLMs, to explore sources, documents and data to increase relevancy of search and data extraction.

• (Personalized) marketing campaigns: AI can analyse customer data to create highly personalized marketing campaigns, resulting in improved customer engagement and higher conversion rates.

• Content recommendation and creation: AI generates relevant, high quality and engaging content, text, speech, and images to customers based on their preferences and assists in generating content for blogs, social media, white papers. and advertising that effectively resonate with the target audience. Image AI can translate text into images and customize existing images. Speech AI converts text-to-speech, make voice edits (e.g., audio production), and can produce voice clones.

• Customer support chatbots: AI-powered chatbots provide prompt customer support, addressing inquiries and issues efficiently to improve customer satisfaction in the B2B e-commerce space.

• Data-driven insights for competitor analysis: fast and efficient analysis and summaries of competitor strategies, news, and trends in the B2B space. This information can inform your marketing strategy and help identify opportunities e.g. to support short term sales initiatives

The greatest value for organizations will come with the customisation of the off-the-shelf models when they are enhanced with company own data to go beyond generic or prompted use cases. This will upscale the benefits in targeted personalization, decrease time used and combine creativity with (company relevant) facts.

However, when implementing GenAI and LLMs in marketing and sales, several substantial challenges must be addressed early to harness the capabilities of the new technology.

• Data Privacy, security and intellectual property: safeguarding customer data, especially when using AI to personalize marketing efforts, while adhering to evolving data protection IP regulations

• Bias and fairness, legal and ethical considerations: identifying and mitigating biases in AI-generated content to ensure that marketing materials do not perpetuate harmful stereotypes, and that content complies with laws and ethical guidelines

• Customization and fine-tuning: tailoring AI models to the specific needs of marketing and sales campaigns, industries, and target audiences, and respecting e.g. product liabilities and warranties

• User experience: designing AI-driven marketing and sales materials that resonate with customers, offer value, and provide a seamless experience

• Integration: integrating AI into existing marketing and sales systems, including customer relationship management (CRM) tools and e-commerce platforms.

• Technical expertise: developing in-house expertise or partnering with experts to effectively leverage GenAI and LLM in marketing strategies

To initiate the integration of GenAI and LLMs, organizations should begin with a business-focused trial-and-error approach including measuring KPIs and prioritize talent development to address AI challenges by investing in injecting practical and technical expertise and providing AI training across various departments. Larger companies should also prepare and share proprietary data, establishing a robust tech foundation and encourage ecosystem innovation. Ensuring compliance with responsible AI practices is of utmost importance: recognizing the evolving landscape of AI-related roles and conducting assessments to understand AI's impact on existing jobs will enable organizations to create a strong foundation for seamless integration, keeping up with AI's transformative potential. The recently released World Economic Forum white paper, Jobs of Tomorrow3), developed together with Accenture, states that 22% of tasks in the marketing function show high potential to be automated (33% for customer sales), 34% (34%) show potential for augmentation, while 41% (16%) show low potential.

The biggest challenge is neither technology nor the selection of relevant use cases but the maturity of your organization to recognize and embrace the new technology. The human side, as always, in transformational situations will determine whether your organization is able to capitalize on the technology and gain a competitive edge (see my Blog on Transformation)

This is fully in line with one key take away from last year’s conference - the winning combination for digital commerce is a hybrid system of human & digital. Investments in upskilling the organization is a must investment and to upskill your organization in order to harness the potential of LLMs effectively, you must begin by evaluating existing skill gaps. Comprehensive education and training programs, the creation of cross-functional teams and a pro-active attitude will support a holistic approach. Encouraging practical experience through real-world projects and fostering a culture of innovation and learning while simultaneously implementing key performance indicators to measure the impact of LLMs will ensure maximum leverage of these new technologies for your business.

1) Unit 8, Generative AI Cut through the Hype and achieve real Business Value
2) Accenture - A new era of generative AI for everyone, 2023
3) WEF, Jobs of Tomorrow, Large Language Models and Jobs, September 2023