TechTonic Shifts Prepare for the “AI-first” businesses.

Somehwere in April, I wrote this article on how AI would evolve over time: A model for strategy development in the AI age. In the third phase of the model we will witness the arrival of Machine Customers, and also the first wave of AI-First businesses.

Here is the article on Machine Customers if you want to know more about what it is.

According to a survey by Deloitte (just Google it), 43% of CEOs have already hopped on the genAI bandwagon. They’re using it to drive “innovation” (Slapping an impaired chatbot on your Customer Care does not count as innovation, people), or – in case they are really into it – automate or streamline tasks in people’s daily work.

That’s all fine and dandy…

Because this is just the beginning.

Generative AI’s superpowers not only lies in generating content, or automating tasks, or analyzing information.

Nope.

It is going to make organizations completely rethink their approach to digital transformation.

Gone are the days of just slapping technology onto existing processes.

Now, it will be all about reimagining business transformation from the ground up. And that will be a game-changer!

For those who have ears, listen up!

The potential for AI to drive business transformation is off the charts.

CEOs have a crucial role to play right now. They need to put on their visionary hats and they need to start articulating a clear vision for how AI can enhance, automate, and augment work (starting by looking at the picture below, and the explanation at the bottom of this article).

The way AI will play out over the coming one to two years time. Explanation at the end of the article

And they can’t forget to invest in value creation and innovation. Organizations need a bold, innovative vision for the future of work on both Machine Customers and AI-First businesses, or they risk falling behind as competitors zoom ahead. And by simply doing nothing, they are setting the stage for future self-inflicted disruption.

And that’s ok.

Evolution favors the one that adapts to change. And major disruption is upon is.

The coming of the AI-First businesses

If you’ve read my articles on AI-Assistants (also called Agentic AI, or Autonomous Agents, or any combination), you are well aware that AI can do way more than just generate funny pictures or act as an impaired Customer Service Rep.

The step before a business, 100% driven by AI is that of the AI-Assistants.

And as soon as we have mature enough platforms that have a no-code, and work-flow based approach to building AI-Assistants, the door to AI-First businesses is wide open.

Now, let me explain what an AI-first business will be all about.

Basically, it is a company where AI is the foundation for everything they do.

I could stop here. But just for the kicks, let me continue.

It’s not just a fancy add-on or a cool new tool—it’s the very essence of how they operate. Because in an AI-first business, every workflow starts with the assumption that AI can be applied.

AI is the default, the go-to solution. because non-AI workflows are only developed when the risk of using AI is too high.

An example

Let’s take a sales and marketing department as an example. In an AI-first approach, AI would be calling the shots. It would determine which audiences are most likely to convert, and it would craft the perfect sales pitch for different groups. It would generate messages that are tailored to increase response rates. AI would even rank incoming sales leads and automatically engage with customers through chat or email to help seal the deal.

If you think that is going to happen far into the future. Think again. The first fully AI-powered funnel management platforms have hit the market. Even Adobe has hopped on the band wagon for B2B sales. Every stakeholder in the sales cycle gets to see different content.

And that’s just the tip of the iceberg! AI can also create customer profiles, schedule meetings, generate reports and forecasts, monitor the competition, and so much more.

It’s a whole new world of possibilities for businesses that are ready to embrace an AI-first mindset.

Before we start!

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AI-powered business transformation

AI-powered business transformation is still in its early days.

AI-powered business transformation will play out over the longer-term, with key decisions required at every step and every level. Even today, we are still early in realizing and defining the potential of the future of work. The future still requires its dreamers and architects.

To achieve AI excellence and accelerate business transformation, you could apply lessons learned from today’s organizations setting the pace:

Engage Leadership in AI Integration:

Senior executives should lead AI implementation and ensure it aligns with strategic goals. A Chief AI Officer – or a Chief Digital or Data Officer tasked with this would also work.
Leaders drive transformation from the top because executive involvement is crucial for successful AI integration and achieving high maturity in AI capabilities.

Establish Governance for AI:

Ok, I personally hate this word, cause it implies everything I have a distaste for as an entrepreneur – bureaucary and the likes – but it is a necessary evil. Because if you let AI rummage through your organization, you’ll end up with a lot of shadow AI (read the article on the topic)

Develop and enforce governance policies to prevent AI from accessing restricted data or making unauthorized decisions.
Implement checks and balances to make sure that AI insights are used responsibly and do not lead to harmful consequences.

Connect People, Data, and Processes Using AI:

Implement AI to streamline and integrate data flows across various functions. Think of payroll, procurement, employee requests, customer queries, and content creation, just to name a few.
Make sure that AI systems support or accelerate routine tasks. That will lead to an improvement of the overall efficiency throughout your company.

Scale Process Improvements with AI:

Adopt an enterprise AI platform to facilitate collaborative efforts and streamline processes.
Integrate AI across customer service, technical support, and customer interactions to speed up responses and allow employees to focus on more value based tasks.

As companies scramble for AI maturity, composure, vision, and execution become key.

Pacesetters may have the early lead, but the race has just begun. This is the time to make your move.

Don’t be left in the AI dust!

Why an “AI-first” business plan will produce stratospheric startups

In new business use cases where AI is the default, or where AI is even the only way an organization functions, the potential results are absolutely phenomenal.

But I believe that humans should still play a key strategic role.

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. It’s like having a super-intelligent chess partner!

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.

Talk about a stock market darling! (NVIDIA, Tesla, Meta, Alphabet?)

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.

Better safe than sorry, right?

To illustrate this AI-first approach, let’s think of ten use cases for say, 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 absolutely massive.

A rough analysis (made with ChatGPT) suggests as much as 50 percent of human time spent on marketing tasks can be replaced with AI.

Companies that are not AI-First, but AI-Augmented, 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 also 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.

Did I just write… “human value add”?

OMG !

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.

The human augmentation will be all about keeping AI on the straight and narrow!

To finish this rather lengthy article (I’m so sorry), AI-first businesses are the future, and the potential for growth and innovation is truly limitless.

Companies should investigate now, how both Machine Customers, and AI-Augmentation will work for them in one to max two years time. Because by next year we will be seeing the first signs of AI-First businesses. And it’s not only me that is saying this.. read the article about this former OpenAI employee about the future of AI.

The race is on, and those who know how to wield the power of AI will be the ones to reap the rewards and shape the future of business in the years to come.

And if you don’t know how.. you can alsways call upon some assistance.

Well, that’s a wrap for today. Tomorrow, I’ll have a fresh episode of TechTonic Shifts for you. If you enjoy my writing and want to support my work, feel free to buy me a coffee ♨️

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Signing off – Marco