How Does AI Reduce Costs? Discover Effective Strategies for Businesses

Implementing AI helps businesses automate repetitive tasks, increase workflow efficiency, and reduce operational costs, as reported by 82% of early AI adopters. However, for other businesses, implementing artificial intelligence might result in disappointment.

In this article, we will review factors to consider, business strategies, and industry-specific use cases of AI that allow businesses to cut costs and streamline growth.

Understanding AI Cost Savings

By allowing machines to handle data-heavy and repetitive tasks, human workers can focus on high-value assignments, simultaneously allowing businesses to reduce costs.

Contrary to the widespread concern, so far, AI is not replacing workers but is complementing them. From chatbots reducing customer support hours to machine learning helping accurately forecast demand, AI adoption enables you to achieve more with less.

What is AI cost reduction?

AI cost reduction is a measurable decrease in operational costs achieved with AI adoption — for example, saving infrastructure costs with smart resource allocation.

For various industries, AI cost reduction will look different. Within logistics, AI algorithms can help you optimize delivery routes to reduce operational costs. On the other hand, finance-tailored AI can detect and prevent user fraud, allowing companies to cut costs on human compliance monitoring.

Benefits of AI cost saving

AI cost savings is not just about budget relief. AI adoption often leads to better decision-making, faster work, and fewer errors. In the long term, AI algorithms allow companies to reinvest savings into R&D projects and stay ahead of the competition.

How AI solutions can help businesses

For many businesses, AI became irreplaceable virtual assistants that handle routine tasks and detect inefficiencies. As of 2025, the use of AI in business goes beyond, say, quality control for manufacturers or forecasting demand for retail companies.

Even small businesses are jumping in, investing a few hundred dollars into low-code tools like GPT-based support chatbots or AI-based analytics dashboards.

The right investment into generative AI can be a game-changer for your business. The key is choosing the right use case.

Real-World Examples of AI Cost Reduction

With 54% of organizations having implemented generative AI models, many have been able to cut business costs and automate repetitive tasks.

Airbnb: Customer service & Code migration

An early artificial intelligence adopter, vacation rental company Airbnb is rapidly rolling out AI tools to streamline customer service and significantly reduce operating costs. Unlike human customer care specialists, AI is able to speak any language and process extensive documentation in seconds, maximizing service efficiency.

Airbnb has also reported an increase in productivity from using AI within software engineering teams. Recently, the company has completed its first large-scale, LLM-driven code migration, reducing estimated migration time from 1.5 years of manual labor to an impressive 6 weeks.

WPP: Leveraging AI for research and development

A global leader in marketing and advertising, WPP has recently released WPP Open, an AI-powered tool for content creation. WPP Open is expected to dramatically cut costs for marketing and advertising teams by achieving unparalleled scale and speed in campaign creation.

WPP has also announced a collaboration with Stability AI, an AI system able to generate highly realistic images, videos, 3D models, and audio. The company hopes that this AI-based solution will help its clients produce content and test concepts quicker, yielding significant savings.

Amazon: Implementing AI for sales efficiency and marketing

"How does AI reduce costs?" has been a running question at Amazon since the late 1990s. As of 2025, these are some ways Amazon utilizes AI to cut costs and maximize revenue:

• Reduced return percentage. Artificial intelligence tools at Amazon detect damaged goods and give personalized clothes size recommendations, reducing returns by 10%.
• Food quality control. AI-powered computer vision technology detects food items that might spoil soon, allowing the company to resell them faster.
• Predictable demand and supply chain. Amazon uses AI to prognose consumer demand, saving money on shipping and delivering parcels faster.

How Artificial Intelligence Improves Efficiency

Increased efficiency of business operations after adopting AI often comes from routine task automation and faster data processing. AI is much more efficient than people when it comes to analyzing big data, scanning it for anomalies, and predicting data-based trends.

For instance, AI tailored for a supply chain management company can accurately anticipate delays and redirect shipments, letting human teams focus on strategic and creative tasks instead.

Generative AI’s efficiency in customer service

Generative AI is changing the game in customer service thanks to its ability to handle hundreds of inquiries instantly, from "Where is my order?" to troubleshooting issues with the product.

AI algorithms trained specifically for customer service are getting better at understanding human tone, adapting to customer types, and escalating the most challenging issues to human workers.

Software engineering and AI solutions

With the increasing skill gap on the IT labor market, engineering teams hoped that AI could help them reduce the costs of software development. And it does, with tools such as GitHub Copilot or Amazon CodeWhisperer that can generate parts of the code, suggest defect fixes, and even refactor whole features.

Coding AI assistants are also invaluable when you need to create test cases, detect bugs, and plan sprints. These tools have a huge potential for increasing software engineering cost efficiency.

Strategies for Implementing AI Cost Savings

With AI development, your starting point should be business pains and needs, not specific technologies you want to implement. Companies that see the biggest results often follow this path:

1. Identify 1-2 high-impact areas,
2. Test AI and non-AI platforms,
3. Document and compare results,
4. Scale.

Additionally, look into how your teams currently work, so that introducing AI can maximize their efficiency, not create additional challenges.

Identify Key Areas for Optimization

To identify high-impact areas that could benefit from AI the most, define where your business might be losing money, time, and energy. It could be manual data entry, customer support, or product delivery process — each case is unique.

If you lack data to confirm your hypothesis, try using tools such as process mining or involving analysts. The goal is to pinpoint tasks that are defined by clear rules, involve big data, or often repeat themselves, as this is where AI will be most helpful.

Assess Current Infrastructure

Before jumping into AI development, ensure that your existing systems are ready. Some AI platforms require integrations with APIs, usage of large and structured datasets, or cloud computing capabilities, which not every organization has. In some cases, you might need to update or reconfigure your infrastructure before introducing AI.

Data Quality and Accessibility

AI models see their training data as the ultimate source of truth, so it is crucial to ensure its quality. Before AI development, check if your data is clean and structured and whether it adheres to data security best practices. The data should also be collected in a format that can be used for AI training.

Overcoming Challenges and Concerns

The prospect of AI development can raise serious concerns inside organizations. Will it require substantial investments? Will AI replace jobs? How complex will the deployment be? And how does AI reduce costs?

To eliminate any roadblocks, start with smaller projects, involve teams early, and clearly measure any outcomes. AI adoption becomes a lot easier when people see AI as an assistant, not a replacement.

Factors That Impact AI’s Cost

The cost of implementing artificial intelligence can vary significantly, from several hundred dollars a month for a simple chatbot to six-figure prices for a custom machine learning system. The price will depend on several factors:

• Is your use case complex?
• Is your data and infrastructure ready?
• Can an off-the-shelf solution suffice?

Costs for maintenance and monitoring can also add up, which is why ROI planning should happen before coding even starts.

Who is More Cost-Effective: AI or Humans?

AI cost efficiency for some tasks is indeed higher compared to people. A human will never be able to process thousands of emails or customer inquiries in seconds without the help of AI.

However, AI implementation is not about replacing people. Its goal is to reduce resources humans spend on routine tasks so that we can focus on work that requires human-only skills, such as empathy and creativity.

Measuring the Impact of AI Cost Savings

To measure if AI is truly saving money for your business, it is beneficial to focus on the following metrics:

• Immediate cost reductions, e.g. cost per transaction,
• Productivity gains, e.g. processing time,
• Time saved,
• Error reduction,
• Long-term scalability, e.g. customer resolution rate.

Tools such as ROI dashboards or A/B testing can help streamline data analysis and clearly observe AI's impact on your business.

Overall Adoption Rate

According to Gartner, by 2026, more than 80% of enterprises will have used customized AI applications. Even though 63% of AI adopters report increased revenue, the overall adoption rate is highly uneven between industries.

Some businesses move fast, and others lag due to law restrictions, personal resistance, or issues with data quality. However, the trend is clear, and more and more companies are considering different ways they can use AI to generate revenue and reduce costs simultaneously. For instance, in the US healthcare, adopting AI would yield $200-$360 billion in savings yearly.

Investment Trends

More than 40% of executives report that they plan to increase AI investments despite economic uncertainty. With venture capital funding growing for AI startups, enterprises are too investing in AI integration and cloud infrastructure.

The Role of Artificial Intelligence in Cost Savings

Before the rise of AI, cutting business costs often meant laying off workers or cutting budgets. Now, AI can kill two birds with one stone, cutting costs and boosting virtually every part of the business.

Most importantly, the solution is not limited to the big players, allowing even family-run businesses to utilize AI and free up some resources for more important tasks.

AI Solutions for Business Efficiency

Even with general-purpose AI solutions, not every tool will fit every type of business and every need. However, across businesses, the most commonly used solutions include:

• Predictive analytics,
• Robotic process automation solutions,
• Chatbots,
• AI-enhanced data platforms.

These tools will most likely help you iterate faster, make better decisions, and adapt to market changes.

Conclusion

Robotic process automation, natural language processing, and machine learning are not magic tools; they still require thoughtful adoption and investments, however small. If you are wondering, "How does AI reduce costs for my business?", start with defining clear goals of AI adoption and reviewing your current state of data and infrastructure.

With the right setup, AI can not only cut costs but create room for growth and business development. AI specialists at Akveo can help answer your questions and find the best AI use cases for your business. Contact us today to receive a free consultation.

{{form}}

Frequently Asked Questions

Does AI make things cheaper?

In the long term, AI will likely decrease the time and resources spent on manual tasks, inefficient processes, and attempts to reverse human errors. However, the gains from AI implementation often come only after an upfront investment and thoughtful development.

Ultimately, as you observe dramatic cost reduction in, say, your organization's customer support or maintenance, AI-powered solutions will be worth it.

How does AI save money and time?

Compared with people, AI performs better when it comes to repetitive tasks that involve large datasets. For example, sorting thousands of emails or finding a typo in a code file. When businesses delegate such tasks to AI, they can reduce labor costs and reduce the number of errors, ultimately saving money and time.