Author: Katie King
_Katie King_
Reading time: 22 minutes
Synopsis
AI Strategy for Sales and Marketing (2025) offers a guide for how businesses can change. It explains how to move from simple automation to a new way of working called Industry 5.0, where people and machines work closely together. The book teaches you about AI making sales for people, making things very personal for customers, and using AI in a fair way. This helps you build a strong business that is ready for the future. You will learn how to use smart technology to grow your business for a long time, build strong trust, and create real customer relationships.
What’s in it for me? How to use AI for a strong business that puts people first.
The world is entering a new time for industries. The tools you use are no longer just simple helpers. They can now act on their own, talk with others, and even create new things. It’s becoming harder to tell the difference between human thinking and computer logic. This is changing how value is made and traded.
Because of this, we need to look beyond the many daily tech stories. We need to think about something more important: how we build and grow relationships in a world that uses more and more computer systems.
In this summary, we will do just that. You will find a plan to understand this move to Industry 5.0. Here, success means working fast and also understanding people’s feelings. You will learn how to handle the challenges of AI making sales and using AI in a fair way. This will turn possible problems into real strengths for your business. By the end, you will clearly understand how to lead with confidence. You will move from just watching technology change things to actively creating growth that lasts and puts people first.
Blink 1 – How to avoid becoming just like everyone else
Businesses always have a simple goal: to meet customer needs and make money. This has not changed. But how companies do this is changing.
We are moving from Industry 4.0 – which was about computers and automatic machines – to something called Industry 5.0. This new time brings human creativity back. People and smart computer systems work together. They do this not just to be faster, but to make things truly special and to connect with customers more deeply.
But there is a danger here that you should notice.
Stephen Klein, a CEO and teacher, saw a problem in his classes. Students who used common AI tools produced work that all looked the same. The work was good, but you couldn’t tell one from another. For a client, everything seemed similar.
This is the trap of becoming too common. If you only use AI for basic tasks – like cutting costs, making work smoother, or doing the same tasks again and again – your work will become average. Everyone uses the same AI to write similar marketing texts. Your brand’s special way of speaking disappears. You offer nothing unique.
So, how can you avoid this trap?
The answer is to move from basic AI (called AI 1.0) to advanced AI (AI 2.0). AI 1.0 is simply about doing tasks. AI 2.0 is about making human work better – using the technology to help you think. Instead of just writing text or answering questions, AI helps you question your ideas, make your plans better, and create very personal experiences that basic automatic tools cannot. A study of many experts showed that those who worked with AI did not just work faster. They also produced better results. The real value is not in replacing human thinking, but in making it stronger.
Now, where is your company in this change?
Boston Consulting Group created a way to measure progress with three steps. The first is use. Here, the main goal is to do things well and fast. For example, chatbots handle regular questions, and emails are sent automatically. These are important first steps, but they rarely make you better than your competitors.
The second step is change. Here, AI starts to affect your business plans. You stop using it just to do things faster and start using it to do things differently. For example, AI can guess which customers are likely to buy a lot, even before they contact you. Or it can create content that changes immediately for what each person likes.
The final step is create. Here, completely new ways of doing business become possible. For example, online shops run by AI that connect buyers and sellers without people helping. Or brand experiences where digital helpers lead you. You are no longer just improving a process. You are building something that did not exist before.
Moving through these steps is how you avoid becoming a common product and truly use what Industry 5.0 offers.
Blink 2 – How to guess what customers feel
When you reach the stage of creating new business ideas, you need to build entirely new systems. This means you also need a different way of relating to customers. For many years, making things personal for customers was a basic tool. Customers were put into groups based on age, place, or what they bought. Then, content was sent to them.
That way of working is no longer enough. The new way is called guessing how customers feel. It moves from just managing how you work with customers to managing their emotions. The goal here is not to track what someone buys, but to understand how they feel when they buy it.
Imagine a customer calling for help, feeling annoyed and without much time. In the past, a computer program would look for words like “refund” or “cancel.” But AI that uses many types of information works differently. It listens to how their voice sounds, how fast they speak, and even small pauses. When it senses more stress, the system changes instantly.
One large airline has tested customer service bots that automatically speak slower and use kinder words when they hear tension in a caller’s voice. This is making things personal using different signals – reading signs from voice, text, and facial expressions. It delivers something that feels natural and human, even though a machine is doing it.
This deep understanding points to something called Zero UI – where screens and controls disappear. When a smart system guesses your needs based on where you are and what you’re doing, screens, menus, and clicks are not needed. Think about flying. With Zero UI, gates that recognize your face let you board instantly. You walk onto a plane without looking for a passport or ticket. The environment reacts to you just because you are there.
This smartness all around you also works in shops and homes. Smart mirrors or home robots can change lights, temperature, and ideas for products. They do this based on who enters a room and how they seem to feel. The technology becomes unseen, leaving only the useful part.
However, a problem comes up here. Being so close to customers brings real dangers: entering people’s private space and unfairness in computer rules. How can you test very personal, emotion-aware systems without showing private information or accidentally treating some groups unfairly? One answer is fake customer profiles – digital characters made from lots of data. They show how real people act and what they are like, using numbers. Think of them as digital test dummies for your plans.
For example, a bank launching a new system to decide who can get a loan can use fake customer profiles. It can test thousands of applications from different types of people, with different ages, genders, and money situations. This is done without touching real customer data. These tests show if the AI unfairly says no to specific groups, like mothers raising children alone or people who do short-term jobs. This way, any unfairness can be fixed before the system starts.
Fashion shops use similar digital copies to test how different body types might respond to a new fashion advice system. This helps ensure their personalization systems are fair to everyone. This method lets you try new and daring things with guessing customer feelings, while still having something that protects you. It allows you to innovate in bold ways without forgetting what is right.
Blink 3 – How to sell to machines
So, you have learned how to guess what customers feel by testing with fake profiles. You might think the difficult part is over. But now things get strange. The thing you are selling to is about to change completely. Soon, your main customer might not be a person at all. It could be a computer program – an AI helper working for a person. Welcome to AI selling to AI, where personal AIs do more than just answer questions. They agree on deals to buy things, choose from choices, and book services without a human doing anything.
This next step makes sense if you think about how hard everyday life can be right now. For example, scrolling through travel sites for the best flight. Or comparing energy companies to save money. In the time of AI agents, you give all these tasks to your personal AI. You say, “Book me a morning flight to London next Tuesday, within budget.” Your agent then goes into the online market. It talks directly to airline AIs. They bargain, check if seats are available based on what you like, and finish the deal.
For marketers, this creates an interesting problem. Many years of work have gone into making brands look good for human eyes – with emotional headlines and nice pictures. But an AI agent does not care about your colours or smart sayings. It cares about data about data, how prices are set, and scores for being good for the environment. To win here, your brand needs to be “machine-readable.” This means making it easy for machines to understand, with labels that explain things and signs of trustworthiness that an AI can quickly understand.
To keep up with these fast, machine-led deals, marketing work needs to change. It must move from campaigns done by hand to systems that run themselves. This is the self-running sales and marketing system. Think of it like a self-driving car for your sales plans. Instead of waiting for a review every three months to change how much money is spent on ads, this system takes in instant customer information and competitor clues. Then, it creates and runs small campaigns right away. It chooses who to aim for, writes personal messages, and gives out money – all without waiting for a human’s approval.
If customer interest goes down or a competitor drops their price, it fixes itself right away. The system does not just follow a plan; it understands the market and keeps changing. It does this within the rules you have set about what is right and what the plan is.
This speed effectively gets rid of the old way of selling. That slow, expected progress from knowing about a product, to thinking about it, to buying it? That’s gone. In a world where AI helps, the sales process becomes a fast, changing cycle. For example, a business customer is found by a computer rule that guesses on LinkedIn. They then talk with an AI to arrange a demonstration. They receive a business plan made just for them from the self-running system. Then, they agree on contract details through a buying robot – all within 48 hours. The steps are not clear anymore. The goal changes from showing someone a way to creating a quick-reacting system that always surrounds them with what is useful.
The basic systems for this are already being built through shop advertising networks. Amazon, Walmart, Tesco – they are all turning their platforms into advertising systems. They make money from their own customer data. This allows brands to reach customers based on what people actually buy, not just general groups of people. These networks are where this self-running future is being learned. They provide systems that manage everything internally, where AI can track a customer from first seeing something to buying it. This lets your systems learn and make things perfect with great accuracy, which was not possible before.
Blink 4 – How to build a human safety net
When you see these self-running systems get faster, selling at speeds no human could reach, you start to feel worried. You realize: you’ve built a very fast car, but you might be driving it blindfolded.
When computer rules work in a secret way, making millions of choices every minute without anyone checking, there is no room for mistakes. This lack of clarity creates a market where trust becomes your most valuable thing – a ‘trust bonus.’ In a time of fake videos and made-up content, the companies that do well will be those that show how things work. They will clearly mark content made by AI and explain exactly how their computer rules make decisions. Being open and clear becomes a real advantage over others.
Now, there is a strong desire to pretend your AI is more advanced than it is. You might feel pushed to quickly put an “AI-powered” label on every product to get people to put money in your business. But be careful of “AI-washing.” Authorities are already taking action against false claims. One time of promising too much can destroy your good name very quickly. It can also bring fines and punishments, and a strong negative reaction from customers. The risk? Your self-running marketing system starts to make promises your business cannot keep, or even worse, makes up facts that could get you into legal trouble.
So, how do you protect yourself against a machine that thinks faster than you do? You do not wait for a problem – you create a fake one to test.
This brings us to Ethical Testing Teams. This idea comes from computer security. It means putting together a team with people from different departments – like marketers, lawyers, and experts in human behavior. Their only job is to find problems in your system before it is used. These teams do something called looking for made-up information. They purposefully try to trick your AI into making false statements, saying unfair things, or breaking your brand’s rules. They test situations that good computer programs might not find, but human instinct quickly notices. For example, a chatbot accidentally promises a return policy you do not have. Or a pricing rule that treats people in certain areas unfairly. By testing how your brand sounds against difficult questions, you make sure your self-running systems do not go out of control when facing real-life problems.
But technology alone cannot solve a problem created by technology. The best protection is your people.
This means a big change for Human Resources. HR can no longer just do office support work. It must become the main builder of AI knowledge. Hiring a few experts in data is not enough. The goal is to build a team where every employee – from creative leaders to customer service staff – understands the rules for using data and the dangers of unfairness. We are seeing entirely new jobs appear, like the “AI Job Planner.” This person’s job is to plan how human jobs will change when working with digital colleagues. They also find skills that people can use in new ways that machines cannot copy.
This checking by people is very important for making sure all people are treated fairly and included – called DEI 2.0. AI often makes unfairness from old data even bigger. If you give a hiring system ten years of job applications from an industry where mostly men work, it learns to treat women applying for jobs unfairly. To fight this, top companies are building “systems to ensure fairness.” Here, teams with experts from different fields check computer rules for fairness for all different groups of people before using the system. This makes sure that getting things done fast does not mean treating people unfairly.
Blink 5 – The plan to make it happen
Good ideas need a strong base. You cannot just hope an AI plan happens. You have to build the support structure that makes it real. This starts with knowing exactly where you are now.
Before using any new tool, do a true check with something called an AI preparation checklist. This is a detailed check across ten different areas. These include everything from support from top managers to how good your data is, and your rules to keep things fair. Based on your score, you will be in one of three groups. Old way means you are not using AI much – you need basic work. Changing means you are testing small projects but have no clear overall plan. Changing completely means you are already using AI widely to change how you work.
What is the point of this check? It stops you from running before you can walk. Using advanced tech on a weak base costs a lot and makes people feel bad.
Once you know your starting point, the next step is an AI guide book. Think of it as a manual that is always updated – not an old rule book no one reads. A good guide book clearly explains ways to use AI. For example, AI for finding how likely a customer is to buy in sales, or understanding customer feelings in support. It appoints “AI leaders” within teams to encourage people to use it. It also sets regular rules for keeping data private so everyone knows the rules before they start. And it makes you define success with clear numbers – like faster answers or more sales – so you can actually show that the money spent is giving good results.
Now, a guide book means nothing without the right people doing the work. And AI is too important to live only in the IT department. To grow in a careful way, you need an Expert Group from Different Departments. This group brings together leaders from marketing, legal, HR, and technology. This group manages your AI plan together. It makes sure your marketing team’s speed does not go faster than your legal team’s comfort with risk. It ensures that as your tech abilities grow, your management grows with them.
Then there is the outside world. Your plan does not exist alone. Rules are changing differently in different countries very fast. The European Union has strict rules about AI based on risks. This sets a high standard for being open. The United States prefers new ideas and companies making their own rules. China has strong government control over AI development. A plan to follow rules that works in New York might not work in Berlin or Beijing. You have to think about that.
The companies that do well will be the ones that use smart tech in daily work. They will treat AI as a main basic system, not just a fancy extra feature. Build strong guide books. Give power to teams from different departments. Pay attention to changes in rules. When you do that, human ideas and machine thinking stop working against each other and start working together. That’s Industry 5.0, and it is possible for anyone willing to do the work.
Final summary
In this summary of AI Strategy for Sales and Marketing by Katie King, you’ve learned that to do well in the new Industry 5.0, you need to go beyond just being fast. You must treat AI as an important helper. It will change how you sell, market, and earn trust.
The old, step-by-step way of selling is gone. In its place is a fast, changing cycle of information. Here, self-running AI acts for customers to make deals. This means you now have to make your brand easy for machines to understand, as much as for people. As computer rules become less clear, being open makes you stand out most. This creates a benefit of being trusted that shows who the leaders are. Teamwork across different departments like marketing, legal, and HR is very important for managing these tools carefully. Being fast should not mean forgetting what is right or making employees unhappy. The companies that win will be the ones that use smart tech in daily work. They will mix human ideas with machine thinking to create the future.
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Source: https://www.blinkist.com/https://www.blinkist.com/en/books/ai-strategy-for-sales-and-marketing-en