Generative AI (GenAI) has only existed in the mainstream for the past 18 months.

Still in its infancy - a toddler if you will - consumers have been joyfully adopting GenAI in their everyday lives. From meal plans to schedule management and image creation to information distilling. But this year, the industry has seen an uptick in the number of organizations truly investing into GenAI and working out the business value it may have. McKinsey and co. this year released research citing that 65% of respondents report that their organization is regularly using GenAI, almost double the amount from the previous year.

In fact, it would appear that GenAI will hold its incredibly strong usage trajectory with responses suggesting that companies are now using AI in more parts of the business. Half of McKinsey’s respondents say their organizations have adopted AI in two or more business functions, up from less than a third of respondents in 2023. Looking ahead, most respondents (67%) expect their organizations to invest more in AI over the next three years.

How can businesses tap into the revenue opportunity of GenAI?

With adoption growing across enterprise, GenAI is no longer a novelty but instead becoming key to business strategies through upside value creation and cost reduction. AI products are delivering real value and are transitioning from being seen as “shiny new toys” to being positioned as key strategic tools.

The opportunity is huge for businesses that are selling GenAI. Increased usage and appetite acoss sales and product development has led to increasing spend, and more and more businesses are building platforms in-house to commercialise.

According to McKinsey, there are three main archetypes for implementing GenAI solutions:

• Takers use off-the-shelf and publicly available solutions
• Shapers customize these tools with proprietary data and systems
• Makers develop their own foundation models or products from scratch

Currently, the business functions or departments getting the most immediate value from GenAI are marketing and sales, product and/or service development, and across IT. But there are use cases across other functions such as operations, software engineering, risk, and strategy.

The biggest increase in usage from 2023’s research is found in marketing and sales, where adoption has more than doubled. However, despite the uptick, the data is still light for use cases, suggesting there is space to carve out for GenAI companies selling into these departments, as well as those that may be unaware of how they could use - and benefit from - GenAI in their own business functions.

The risks GenAI brings to businesses

With opportunity, often comes risk. GenAI is changing the way businesses operate but it’s also introducing new categories of risk into a business. These risks are varied and can include intellectual property infringement, data privacy, bias, inaccuracy, security, regulatory and reputational damage.

Despite the increased usage, GenAI is still very much in the experimentation phase for businesses and consumers alike. Depending on the industry, a number of businesses are using readily-available, out-of-the-box GenAI products rather than custom designed solutions which takes away the competitive edge as more and more businesses use the same tools. These can be put into use faster, but don’t always serve the business needs in a secure and risk-mitigated manner.

To combat this, organizations are developing governance models which they are taking their AI applications and their suppliers through. Due to the infancy and regulatory nature surrounding AI, it’s taking up to eight months sometimes to put solutions into production.

In response to this increased governance and ever-stretching timeline, businesses that are selling GenAI products are facing the impact of increasing sales cycle lengths and an increased cost of selling.

Defining the playbook on selling GenAI

The playbook on selling a GenAI product is yet to be written, but we are seeing parallels with previous tech regulation breakthroughs. This is the same watershed moment that data protection went through with GDPR - the due diligence model was rewritten and then so too was the enterprise sales playbook.

An interesting finding from McKinsey’s research was around the core difference between “high performance” GenAI users and “regular” users, and how this impacts the opportunity for companies selling GenAI. Around half of the reported AI use cases within business functions are using publicly available products/models/tools - but GenAI high performers are less likely to use those off-the-shelf options and will either customize or build their own.

The main difference between users? Their appetite for risks. High performance users are nearly twice as likely as regular users to involve the legal function and embed risk reviews early on, and they’re much more likely than others to employ a wide range of best practices - from strategy to scale.

Figuring out how to navigate a customer’s governance requirements quickly, repeatedly, and at scale is going to be critical in growing a GenAI business, and platforms that help you manoeuvre requests at speed will be crucial to closing deals.

Platformed ensures every sale and every renewal is built on a platform of trust. It is designed for B2B leaders in enterprise and regulated markets, eliminating delays from due diligence questionnaires and RFPs.

Its AI-powered toolkit syncs data from policies, past questionnaires, and audit reports to automate responses and streamline reviews. Platformed supports seamless import/export in any format, maintains a constantly updating knowledgebase, and requires no intrusive integration. It handles diverse legacy systems, saves time, manages complex queries, and provides a comprehensive evidence stream for each response.

If you sell GenAI products to enterprise organizations and have to balance multiple RFPs and questionnaires per month, Platformed can help you build your internal playbook. Sign up for a demo with our team of experts, or get in touch to find out more.