How can busi­ness­es improve ef­fi­cien­cy with AI?

Improving ef­fi­cien­cy with AI allows busi­ness­es to save time, automate routine processes and support employees with everyday tasks. Small busi­ness­es and startups, in par­tic­u­lar, can use AI solutions to make better use of limited resources, stream­line workflows and achieve greater op­er­a­tional ef­fi­cien­cy through AI-driven tools.

What does improving ef­fi­cien­cy with AI mean?

Improving ef­fi­cien­cy with AI means using ar­ti­fi­cial in­tel­li­gence to make business processes faster, more automated and less prone to errors. AI can not only take over repet­i­tive routine tasks, but also support analysis, com­mu­ni­ca­tion, de­vel­op­ment and decision-making processes. While tra­di­tion­al au­toma­tion usually follows pre­de­fined rules, AI can process in­for­ma­tion, identify patterns and adapt to new sit­u­a­tions. This opens up a wide range of possible ap­pli­ca­tions:

• automatic pro­cess­ing of documents
• creation and op­ti­miza­tion of content
• analysis of large volumes of data
• support for customer service
• au­toma­tion of internal workflows

What are the benefits of in­te­grat­ing AI?

Targeted AI in­te­gra­tion can support busi­ness­es in various areas and help improve overall ef­fi­cien­cy.

Startups in par­tic­u­lar can benefit from AI taking over tasks that would otherwise require ad­di­tion­al roles or staff resources.

How can busi­ness­es improve ef­fi­cien­cy with AI?

AI improves business ef­fi­cien­cy, es­pe­cial­ly in areas with many recurring or data-intensive tasks. Many business processes involve manual steps that AI can automate. In par­tic­u­lar, AI ap­pli­ca­tions can provide targeted support in marketing and content creation, customer service and back-office op­er­a­tions.

Marketing and content creation

AI supports marketing teams in creating, adapting and analyzing content, for example by trans­form­ing technical in­for­ma­tion into easy-to-un­der­stand materials. In addition, AI systems can analyze existing code or technical doc­u­men­ta­tion and generate content based on it. Overall, AI can support marketing and content creation through a range of tasks:

• Editorial text creation, e.g. for product de­scrip­tions or blog posts
• Creation of social media posts
• Analysis of target groups
• Per­son­al­iza­tion of marketing campaigns
• Op­ti­miza­tion of texts for different channels

How can AI agents improve customer support?

AI agents allow busi­ness­es to handle customer inquiries around the clock. They analyze requests, access in­for­ma­tion and can resolve simple issues directly. Typical tasks include:

• Answering fre­quent­ly asked questions
• Status inquiries about orders or services
• Support with standard problems
• Automatic pri­or­i­ti­za­tion of support tickets
• AI-supported call center processes

An important area of ap­pli­ca­tion is support triage:

1. A customer inquiry comes in.
2. The AI analyzes the topic and urgency.
3. Simple inquiries are answered au­to­mat­i­cal­ly.
4. Complex cases are forwarded to staff along with relevant in­for­ma­tion.

Depending on the channel, these tasks can be handled by spe­cial­ized AI as­sis­tants: AI Chat Assistant for the website, AI Email Assistant for the mailbox and AI Re­cep­tion­ist for incoming calls.

This reduces pro­cess­ing times and allows support teams to focus on more demanding tasks, sig­nif­i­cant­ly improving AI ef­fi­cien­cy in customer service.

How AI supports back-office au­toma­tion

Internal ad­min­is­tra­tion processes such as invoice pro­cess­ing or knowledge man­age­ment can also be improved through AI ef­fi­cien­cy:

Smaller busi­ness­es in par­tic­u­lar can use AI to reduce ad­min­is­tra­tive effort.

Which AI tools belong in an efficient company tech stack in 2026?

To improve ef­fi­cien­cy with AI, companies often combine different AI tools that support a range of tasks across their daily op­er­a­tions. An AI tech stack can include knowledge work as­sis­tants, de­vel­op­ment tools, workflow au­toma­tion platforms and spe­cial­ized ap­pli­ca­tions tailored to specific business areas.

Example of how an in­te­grat­ed AI workflow improves business ef­fi­cien­cy

A possible scenario for a small business is de­vel­op­ing and launching a new product feature:

1. De­vel­op­ment with AI support

A de­vel­op­ment team uses, for example, GitHub Copilot to write code faster, analyze errors and document technical changes.

2. Preparing in­for­ma­tion with an AI assistant

The technical in­for­ma­tion is then processed using an AI assistant. It can help turn bullet points into clear product texts, internal summaries or initial drafts for com­mu­ni­ca­tion materials.

3. Au­tomat­ing the workflow

Using a platform such as Make, an automated process can then be set up. For example, new doc­u­men­ta­tion can be au­to­mat­i­cal­ly forwarded to the relevant teams or in­te­grat­ed into existing systems.

4. Spe­cial­ized content op­ti­miza­tion with AI

A marketing team can then use, for example, Jasper or a com­pa­ra­ble AI-based content tool to adapt content for different channels, such as the website, newslet­ter or social media.

By combining these tools, busi­ness­es can create a con­tin­u­ous AI-supported workflow that covers the entire process: from de­vel­op­ment and internal pro­cess­ing to automated content dis­tri­b­u­tion and marketing.

How do companies integrate AI into their workflows?

A suc­cess­ful AI im­ple­men­ta­tion starts with analyzing existing processes rather than simply choosing a tool. The following tips can help busi­ness­es select AI solutions that improve ef­fi­cien­cy:

1. Identify suitable processes

Tasks are par­tic­u­lar­ly suitable when they involve:

• high manual effort
• many rep­e­ti­tions
• clear pro­ce­dures
• large volumes of data

2. Define goals

Companies should define which im­prove­ment is to be achieved, for example:

• less pro­cess­ing time
• faster responses to customers
• lower error rate
• higher pro­duc­tiv­i­ty

3. Start with small projects

A pilot project helps to gain ex­pe­ri­ence and assess the benefits. Suc­cess­ful ap­pli­ca­tions can then be expanded step by step.

4. Involve employees

AI works best when employees un­der­stand how to use it ef­fec­tive­ly. Training and clear guide­lines help busi­ness­es implement AI safely and make the most of its potential.

What are the chal­lenges of using AI in busi­ness­es?

Despite its many ad­van­tages, there are areas where companies should not use AI without proper oversight.

• Human oversight remains important: AI can produce incorrect or in­com­plete results. Es­pe­cial­ly for business-critical decisions, outputs should be reviewed by humans.
• Observe data pro­tec­tion and security: Companies should comply with ap­plic­a­ble privacy and security re­quire­ments and consider rec­og­nized AI risk man­age­ment practices, such as the NIST AI Risk Man­age­ment Framework. They should also consider which data is processed, which providers are used and how access is regulated.
• Data quality de­ter­mines the results: AI systems require suitable data and clear processes. In­ac­cu­rate or outdated in­for­ma­tion can lead to poor outcomes.
• Plan costs and effort re­al­is­ti­cal­ly: In addition to license fees, companies may need to consider in­te­gra­tion efforts, employee training and ad­just­ments to existing processes.