Why an “AI-first” business plan will produce stratospheric startups
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- An “AI-first” business is one in which AI is the foundation for how all work gets done.
- Projected “AI-first” use cases for a sales and marketing department reveal massive savings in time and costs.
- People should define the policies within which AI operates — and then let AI move the pieces on the board.
With some imagination and hard work, AI can be applied to increase the financial performance of a business by such a large margin that if the company is publicly traded, its stock price will increase as a direct result of large-scale AI adoption.
For an entirely new business, it is worth considering whether it can be an AI-first business — that is, a business in which AI is the foundation for how all work gets done. In this AI-first approach, every workflow begins with the assumption that AI can be applied. AI is the default, and non-AI workflows are developed only when the risk in using AI is too high.
To illustrate this AI-first approach, here are ten use cases for a sales and marketing department:
- AI determines which audiences are most likely to convert to a purchase.
- AI helps craft the sales pitch, creating multiple versions for different audiences.
- AI generates messages by analyzing the context and selecting from an inventory of possible message imagery and text to increase response rate.
- AI ranks incoming sales leads and then automatically engages in chat or a sequence of email messages to help the customer complete the purchase.
- AI analyzes the sentiment and mood of consumers that the AI is engaging in customer-service chats so that a human customer-service representative can be informed if they need to take over the conversation.
- AI assembles a comprehensive profile of customers or site visitors, including their LinkedIn profile, so that when sales reps make contact, they already know a great deal about them and can quickly build a rapport. If it is a direct-to-consumer business, AI generates a real-time profile of propensity to buy as well as the next action to optimize customer experience and profit.
- AI automatically schedules meetings for sales reps and records and files notes from the meeting. Because missing data are a leading problem in generating accurate sales forecasts, AI handles the busy work of reporting to free up sales people’s time while also improving the forecast.
- AI generates reporting dashboards, financial forecasts, and other sales and marketing analytics, including identifying which customers are most likely to churn and proposing strategies for saving those accounts. In some cases, AI automatically acts on the data signals, informing management of the actions AI has taken.
- AI monitors the new-product roadmap and generates presentations of new features and capabilities (the product-marketing function).
- AI monitors the competition, summarizing its conference presentations, its new products announced on its website, its advertisements, and its social media posts.
The time saving from AI in marketing and sales is massive. Our analysis suggests as much as 50 percent of human time spent on marketing tasks can be replaced with AI. Companies can reduce the costs for marketing and sales and at the same time increase profits. They can redeploy human capital by using AI to free-up marketers’ time so they can focus on higher-value tasks, such as developing a longer-term strategy for the business — a strategy that AI can execute.
Marketers’ value add is setting policy boundaries for the AI to work within. Strategy and policy are important aspects of the human value add because although the AI may find it optimizes profits, it also takes actions that miss the bigger picture. Without human-managed boundaries, AI could increase prices during a natural disaster — which is both illegal and unethical. Price gouging could increase profits but may not be consistent with the business’s values, so a human-set policy that is empathetic to the customer in times of hardship may be a part of the strategy.
Although some see business as akin to a game of chess or Go, and AI is quite good at such games, it seems prudent to have people explicitly tasked with defining longer-term business strategy and the policies within which AI operates and then let AI move the pieces on the board.
