6 Practical Ways to Use AI in Business Right Now

AI tools that existed two years ago were experimental. The ones available in 2025 are production-ready and being used by businesses of every size. The question isn't whether to adopt AI — it's which workflows to tackle first to get measurable ROI.

1. Customer Support Automation

Modern customer support platforms have integrated AI capabilities that can significantly reduce the burden on human agents and improve response times. These tools are not designed to replace human interaction entirely, but rather to augment it by handling routine inquiries and freeing up agents to focus on more complex or sensitive issues.

Tools:

Two leading platforms in this space are Intercom Fin and Zendesk AI. Intercom Fin focuses on conversational AI within the Intercom platform, allowing businesses to automate a large portion of their customer interactions. Zendesk AI provides a broader suite of AI-powered features across the Zendesk ecosystem, including automated ticket routing, sentiment analysis, and intelligent knowledge base suggestions.

Implementation:

A practical implementation strategy involves deploying these AI tools for Tier 1 queries, which are the most common and repetitive questions that customers ask. Examples include FAQs, order status inquiries, and password resets. The AI can be trained on a knowledge base of common questions and answers, allowing it to quickly and accurately respond to these inquiries. For more complex issues, such as billing disputes, technical issues requiring in-depth troubleshooting, or any emotionally charged conversations, the AI should be configured to escalate the interaction to a human agent. This ensures that customers receive the appropriate level of support for their specific needs.

Deflection Rate Target:

A reasonable target for deflection rate, which is the percentage of tickets that are resolved by the AI without human intervention, is 30-40% of total ticket volume. This means that the AI should be able to handle a significant portion of the routine inquiries, freeing up human agents to focus on more complex and valuable tasks.

ROI:

Teams using Intercom Fin have reported a 35% reduction in tickets requiring a first response from a human agent. This translates to significant cost savings in terms of reduced agent workload and improved response times. Furthermore, by automating routine inquiries, businesses can improve customer satisfaction by providing faster and more consistent support.

When NOT to use it:

It's crucial to avoid automating interactions that require a personal touch or a high degree of empathy. For example, renewal conversations or churn-risk interactions should always be handled by human agents. These interactions are critical for building customer loyalty and preventing customer attrition. Automating them can lead to a negative customer experience and ultimately damage the relationship.

2. Sales Outreach Personalization

Personalized sales outreach is crucial for cutting through the noise and capturing the attention of potential customers. AI can be a powerful tool for automating the research and drafting process, allowing sales representatives to create more targeted and effective outreach campaigns.

Tools:

A powerful combination involves using Clay, a data enrichment platform, in conjunction with GPT-4, the advanced language model from OpenAI. Clay can pull data from various sources, such as LinkedIn, news mentions, job postings, and company signals, to create a comprehensive profile of each prospect. Apollo AI is another strong contender, offering integrated AI features within its sales intelligence platform.

Implementation Workflow:

The implementation workflow involves using Clay to gather relevant information about each prospect and their company. This information is then fed into GPT-4, which drafts a custom first paragraph for the outreach email. This paragraph should reference a specific trigger, such as a recent funding round, a product launch, or a hiring signal. The sales representative then reviews the draft, makes any necessary edits, and sends the email. The key is to use AI for research and first-draft creation, not for sending AI-generated content unreviewed.

ROI:

By personalizing sales outreach, businesses can expect to see a 2-3x increase in response rates compared to templated sequences. This is because personalized emails are more likely to resonate with prospects and demonstrate that the sales representative has taken the time to understand their needs and interests.

The Key:

The key to success is to use AI as a tool to augment human intelligence, not to replace it. AI can automate the time-consuming task of research and drafting, but the sales representative must still review and personalize the content to ensure that it is accurate, relevant, and engaging. Sending AI-generated content unreviewed can lead to errors, inaccuracies, and a negative customer experience.

3. Content Production (Not Replacement)

AI has the potential to revolutionize content creation, but it's important to remember that it's a tool to augment human creativity, not to replace it entirely. AI can automate many of the tedious and time-consuming tasks involved in content production, freeing up human writers to focus on more strategic and creative aspects.

Tools:

Popular tools for AI-assisted content creation include Claude, Gemini, and Jasper. These platforms offer a range of features, such as automated content generation, grammar checking, and style suggestions. They can be used to create a variety of content formats, including blog posts, articles, social media posts, and marketing copy.

Implementation:

A practical implementation strategy involves using AI to draft the outline and first draft of the content. The human editor then rewrites the content to ensure that it has a consistent voice, adds original examples, fact-checks any statistics, and optimizes it for SEO. The best practice is to never publish AI-generated content without editing. AI excels at structure, transitions, and covering standard ground. Humans add proprietary data, genuine opinions, and specific case references.

ROI:

When done right, AI-assisted content creation can reduce the time-per-piece by 40-60%. This translates to significant cost savings in terms of reduced writer workload and increased content output. Furthermore, by using AI to automate some of the more mundane tasks, writers can focus on creating higher-quality and more engaging content.

Best Practices:

It's essential to remember that AI is a tool, not a replacement for human creativity. AI can help you generate content faster and more efficiently, but it's up to you to ensure that the content is accurate, engaging, and relevant to your audience. Always review and edit AI-generated content before publishing it. Add your own unique voice, perspective, and insights to make the content truly valuable.

4. Internal Knowledge Base and Search

A well-organized and easily searchable internal knowledge base is essential for employee productivity and efficiency. AI can significantly improve the accessibility and usability of internal knowledge bases by providing a more intuitive and natural way for employees to find the information they need.

Tools:

Several tools can be used to create an AI-powered internal knowledge base, including Notion AI, Guru, and custom GPT solutions built on internal documentation. These platforms allow employees to ask questions in plain English and receive accurate answers with source links.

Implementation:

The implementation process involves indexing existing documentation, such as Confluence pages, Notion databases, and Google Drive files, into a Retrieval-Augmented Generation (RAG)-based system. This allows employees to ask plain-English questions and receive accurate answers with source links. The system uses AI to understand the meaning of the question and retrieve the most relevant information from the knowledge base.

ROI:

Guru's 2024 benchmark data indicates that an AI-powered internal knowledge base can reduce the average "where is that doc?" time from 8 minutes to under 60 seconds. This translates to significant time savings for employees and increased productivity for the organization.

Works Best When:

An AI-powered internal knowledge base works best when the underlying documentation is structured and well-maintained. If the documentation is outdated or contradictory, the AI will struggle to provide accurate answers. It's essential to clean up and organize the documentation before indexing it into the system.

Doesn't Work Well On:

Avoid indexing outdated or contradictory documentation. Fix the source before indexing it. The AI will only be as good as the data it's trained on. Garbage in, garbage out.

5. Automated Reporting and Data Summaries

Data analysis and reporting can be time-consuming and tedious tasks, especially for teams that are drowning in dashboards and spreadsheets. AI can automate the process of generating reports and data summaries, freeing up analysts to focus on more strategic and value-added activities.

Tools:

Several business intelligence (BI) tools have integrated AI capabilities, including Power BI Copilot, Tableau Pulse, and Hex AI. These tools allow users to connect to their data sources and generate automated summaries of key metric changes.

Implementation:

The implementation process involves connecting the BI tool to an AI layer and setting up weekly automated summary triggers. The AI then generates a plain-English narrative of key metric changes, which is delivered to Slack or email. This allows executives and other stakeholders to quickly understand the key trends and insights without having to wade through complex dashboards.

Who This Works For:

This approach works best for operations teams that are drowning in dashboards and executives who need signal, not charts. It provides a concise and easily digestible summary of the key data points, allowing them to make informed decisions quickly.

ROI:

AI-powered automated reporting can save 2-4 hours per week per analyst on routine report narration. This translates to significant cost savings and increased efficiency for the analytics team.

Caveat:

AI-generated summaries still require a human to validate before sharing externally. The AI may not always capture all of the nuances and complexities of the data, so it's important to have a human analyst review the summary to ensure that it's accurate and complete.

6. AI-Assisted Hiring and Candidate Screening

Hiring is a critical process for any organization, but it can also be time-consuming and expensive. AI can automate many of the tasks involved in hiring, such as generating job descriptions, screening resumes, and scheduling interviews, freeing up recruiters to focus on building relationships with candidates and making informed hiring decisions.

Tools:

Several AI-powered hiring platforms are available, including HireVue, Workable AI, and Ashby. These platforms offer a range of features, such as automated job description generation, resume screening, candidate scoring, and interview scheduling.

Implementation:

The implementation process involves using AI to generate role-specific job descriptions from a structured brief, screening inbound resumes against defined criteria, scoring candidates, flagging the top 20% for recruiter review, and generating role-specific interview question banks. This helps to streamline the hiring process and ensure that recruiters are focusing on the most qualified candidates.

ROI:

AI-assisted hiring can reduce time-to-shortlist by 40-60% on high-volume roles. This translates to significant cost savings in terms of reduced recruiter workload and faster time-to-hire.

Compliance Note:

AI screening must be audited for bias regularly. Document your screening criteria and review rejected candidates periodically. It's crucial to ensure that the AI is not discriminating against any protected groups. Do not use AI as the sole decision-maker in hiring. The AI should be used as a tool to assist recruiters, not to replace them entirely.

What AI Still Can't Do

While AI has made significant strides in recent years, there are still many things that it cannot do. It's important to understand the limitations of AI and to use it appropriately.

• Managing relationships that require trust built over time
• Making ethical judgment calls with ambiguous context
• Creative strategy that requires genuine market intuition
• Navigating organizational politics or sensitive negotiations
• Replacing accountability — someone still owns outcomes

AI is a powerful tool, but it's not a magic bullet. It's important to use it wisely and to understand its limitations. Human judgment, creativity, and empathy are still essential for success in many areas of business.

Valueans builds AI-integrated products for businesses that want measurable results, not experiments. ClinchRev, our AI voice dialer, is one example of what production-ready AI integration looks like in a real sales workflow. If you're evaluating how AI fits into your product or internal operations, we can help you build it right.