Generative AI – Transforming Marketing, Sales, and Service

(Generative) AI (Generative) AI Blog article Blog article Whitepaper

Author: Jan Pilhar, Executive Director, IBM iX

a woman holding a phone in her hands, looking at it. Behind her is a graphic with different symbols featuring a rocket, another phone and a brain.

Generative AI is firing people’s imaginations across virtually all sectors. As one of the most transformational technologies of our time, it is changing the nature of many areas of business – not least marketing, sales and services. That being said, it is highly challenging to deploy, so it is well worth pursuing an end-to-end approach. Acting prudently can help users harness the technology’s full potential while avoiding pitfalls.

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Generative AI enables organisations to streamline, speed up and optimise any number of processes. As well as greater efficiency, it promises to offer a better experience for customers – equating to genuine added value. Now is the time to get to grips with this technology and gain a competitive edge. But what exactly does “generative AI” mean? Where can it best be employed? And what strategic steps and challenges are involved in implementing it?

Generative AI is a key new development in the field of artificial intelligence. While conventional AI models are optimised primarily to complete specific tasks, generative AI can cover many use cases and produce new content – especially in the field of natural language. The primary bases for this are foundation models (FM) and, in particular, large language models (LLM), which can analyse and summarise complex content and unstructured data, and facilitate the creation of new content in the form of text, images and software code.

Ample use cases in Marketing, Sales, and Services

The hype is entirely deserved, as the technology has the potential to change digital experiences from the ground up. From optimising marketing to digital commerce and customer service, it has many different applications. When it comes to marketing, for example, generative AI can help companies design and optimise creative assets, analyse customer data more effectively and use this analysis as a basis to pursue a more suitable personalisation strategy. In content production and design in particular, the technology enables completely new workflows that take digital experiences to an entirely new level. In digital commerce and sales, generative AI can help put the most relevant products into the hands of specific customers, increase conversion rates and optimise resource planning (e.g. in-house sales teams). With regard to customer service, generative AI uses intelligent automation to make processes more cost-efficient while increasing the quality of customer support.

Harnessing potential in the right way

Many companies want to take advantage of the opportunities provided by generative AI as quickly as possible – partly owing to a fear of missing out on the next big thing. Two out of three CEOs feel they are being pushed by their investors to act quickly, while the same proportion of CMOs would like to deploy generative AI solutions within the next 12 months. Despite the euphoria and need to act quickly – both of which are justified – it is important to have a clear strategy for the technology. This is evident from looking at the latest data on AI investments, which shows how many AI projects ultimately fail to translate into a desired level of economic success. Up to now, company-wide AI initiatives have generated an average ROI of just 5.9%. The right strategy can help companies circumvent typical stumbling blocks and use generative AI in a way that creates maximum value.

Overcoming challenges

While generative AI has impressive features and can be employed in many different areas, it does come with a few challenges. Alongside technological aspects such as data retention, model and tool selection, and development environments, a key factor for the success of the technology is trust. Generative AI will only achieve its stated goals if employees and customers feel they can rely on the results. This is why such systems themselves need to be precise, transparent and comprehensible. Many solutions today are effectively black boxes, meaning their decision-making capabilities are hidden from people, thus leading to legitimate concerns about responsibility and fairness. Copyright, security and data privacy are three other key issues that should be addressed.

The future belongs to the early adopters

Despite these challenges, generative AI promises to revolutionise the digital experience, including in marketing, sales and services. Companies that take advantage of the new opportunities early on and manage to clear the many hurdles along the way can gain a clear competitive advantage. Doing so calls for a consistent strategy and the right partner. We can be that partner for you!