What 6 Novels Can Teach Us About the Future of AI

Right now, artificial intelligence feels both exciting and a little confusing.

Ask different people about artificial intelligence, and you’ll hear everything from promises of transforming or replacing engineering to fears of a future straight out of science fiction. Writers have explored these ideas for years. Before generative AI became common, they pictured intelligent machines as friends, helpers, judges, and villains. What makes these stories interesting now isn’t whether they got the future right, but how they reflect our ongoing curiosity and concerns about AI.

But not all fictional AIs are alike. Some are similar to the systems we use today, while others envision machines that can reason as widely as humans, or even more. Noticing these differences makes the six novels below even more fascinating.

Researchers generally describe AI in three categories:

• Artificial Narrow Intelligence (ANI): The AI we use today. These systems perform specific tasks exceptionally well but cannot move beyond the purpose for which they were designed.
• Artificial General Intelligence (AGI): A theoretical system capable of learning and reasoning across unfamiliar situations, much like a person can.
• Artificial Superintelligence (ASI): A speculative future in which AI surpasses human intelligence across virtually every domain.

Only the first type of AI actually exists today. The other two remain ideas, which is why they make such great material for fiction.

Each of these novels explores the same three questions in its own way:

• Can we trust machines?
• Can we trust the people who build them?
• Can we trust ourselves when we rely on them?

Culpability by Bruce Holsinger

After a semi-autonomous family minivan causes a deadly accident, the driver’s mother, who works as an AI ethicist, must figure out who is really responsible. As the investigation progresses, the accident brings out hidden tensions in the family, and each person has to face tough questions about responsibility, memory, and the choices that led to a tragedy no one anticipated.

The AI in Holsinger’s story feels familiar because it’s like the specialized systems we use every day. The novel doesn’t focus on whether the software made the right choice; instead, it asks whether people can or should assign moral responsibility to an algorithm. It’s a thoughtful reminder that even simple AI can change how we think about accountability.

The Proving Ground by Michael Connelly

Attorney Mickey Haller takes on a modern case when an AI chatbot is blamed for encouraging a teenage boy to murder his ex-girlfriend. What starts as a wrongful death lawsuit soon becomes a look at tech companies, product responsibility, and what can happen when AI is released into people’s lives before we fully understand the risks.

Like the AI in Culpability, the chatbot here is narrow intelligence, no different in kind from a recommendation engine or a customer service bot. Connelly’s point is that even ANI can have an outsized real-world impact when people trust it more than they should.

Hum by Helen Phillips

In Phillips’ vision of the near future, robotic ‘hums’ slowly become part of everyday life while a regular family tries to adjust. Phillips mixes the strange new technology with a close look at family life, asking what it means to stay connected when convenience means giving up privacy and independence.

The hums are technically ANI, built for specific tasks, but they behave with enough empathy and judgment to blur the line toward something more. That ambiguity, not a clear answer, is what makes the novel compelling.

Machines Like Me; and People Like You by Ian McEwan

Adam, one of the first synthetic humans, does more than just answer questions or do chores. He creates his own sense of right and wrong and sticks to it. The story takes place in an alternate version of the UK and uses Adam’s character to explore love, truth, justice, and whether perfect logic can really work with messy human relationships.

McEwan’s version of artificial general intelligence isn’t scary because Adam is strong. It’s unsettling because Adam’s steady morals highlight the contradictions in the people around him.

Klara and the Sun by Kazuo Ishiguro

Klara, an “artificial friend,” watches the world with great patience and kindness as she looks after a chronically ill child. The story is told through Klara’s eyes and explores her efforts to understand the people around her and the delicate relationships that show what it means to care for someone.

Klara reads more like AGI than ANI. She reasons, adapts, and forms judgments well outside her original task. But Ishiguro’s real question isn’t technical: If a machine shows loyalty, hope, and sacrifice, does it matter whether those feelings are real or programmed?

Annie Bot by Sierra Greer

Annie starts out as a product made to meet someone else’s needs. As she slowly changes her programming, she begins to find her identity. When Annie becomes more aware of what she wants and what holds her back, the story moves from science fiction to a very human look at independence, identity, and the power imbalances that affect relationships.

Greer makes Annie’s journey from narrow intelligence to real independence a very personal story. Technology is important, but the novel is really about identity, control, and what happens when artificial intelligence pushes past the limits set for it.

Why this matters outside of fiction

These novels picture many different futures, but they all return to one main question: What happens when we let machines make important decisions? Today’s AI is nothing like the general or superintelligent systems found in fiction. Instead, we have powerful tools that also show their limits. They can spot patterns, summarize information, and speed up routine tasks, but they still need reliable data, clear goals, and human judgment.

That brings us back to the third question these novels keep asking: Can we trust ourselves when we rely on machines? For engineers, that question isn’t abstract. AI can draw on years of product knowledge, but it can’t replace the experience needed to weigh options, assess risks, or make tough decisions. That’s why manufacturing focuses more on context. For example, product lifecycle management connects requirements, designs, changes, and decisions in a digital thread. Well-managed engineering knowledge provides AI with reliable information to use, while people remain responsible for the choices that shape products.

Maybe that’s the biggest difference between fiction and real life. The novels wonder whether machines will ever think like people, but today’s challenge is more practical: Are we creating the connected knowledge, reliable information, and strong engineering habits that let AI become a truly helpful partner?

How we answer that question will shape our future long before any kind of “artificial superintelligence” appears.

If you’ve read an AI novel that changed how you think about technology, trust, or the future, we’d love to hear about it. Every good book starts a conversation, so please share your thoughts in the comments below.