Consider you’re running a small business and feeling overwhelmed. There’s so much to do that you’re falling behind. Suddenly, your nervousness turns to excitement with the knowledge that AI can help you work faster and smarter, relieving stress. But then you stumble across a blog that mentions ‘AI agents’, and you feel your excitement drain. What is an ‘AI agent,’ and how can it help my business? You're in the right place if you’ve asked yourself similar questions. In this guide, we’ll answer the question, “How can AI help my business?” while explaining the ins and outs of AI Agents and how they can help your business. You’ll learn to build trustworthy AI systems to enhance your business operations and improve your bottom line.

As you’ll discover, OpenSesame's AI Agent Infrastructure can help you reach your goals. This solution can help you create the most effective AI Agents to meet your business needs.

What Is AI?

Artificial intelligence (AI) mimics human intelligence functions by machines, particularly computer systems. AI applications include expert systems, natural language processing, speech recognition, and machine vision. As the excitement around AI has increased, vendors have rushed to market how their products and services incorporate it. 

They often refer to "AI" as a well-established technology, such as machine learning. AI needs specialized hardware and software for writing and training machine learning algorithms. No single programming language is used exclusively in AI, but Python, R, Java, C++, and Julia are all popular languages among AI developers. 

How Does Artificial Intelligence Work?

AI systems generally work by ingesting large amounts of labeled training data, analyzing that data for correlations and patterns, and using these patterns to make predictions about future states. For example, an AI chatbot fed examples of text can learn to generate lifelike exchanges with people, and an image recognition tool can learn to identify and describe objects in images by reviewing millions of examples. Generative AI techniques have advanced rapidly over the past few years and can create realistic text, photographs, music, and other media. 

Programming AI

Programming AI systems focus on cognitive skills such as learning. This aspect of AI programming involves acquiring data and creating rules, known as algorithms, to transform it into actionable information. These algorithms provide computing devices with step-by-step instructions for completing specific tasks. Reasoning. This aspect involves choosing the suitable algorithm to reach a desired outcome. Self-correction. 

This aspect involves algorithms continuously learning and tuning themselves to provide the most accurate results possible. Creativity. This aspect uses neural networks, rule-based systems, statistical methods, and other AI techniques to generate new images, text, music, ideas, etc. 

Benefits of AI For Businesses

Enhanced Operational Efficiency 

AI can perform repetitive tasks, allowing employees to focus on more impactful work. This shift streamlines workflows and eliminates tedious manual processes. The outcome? Boosted efficiency and productivity. 

Consider data entry, document processing, and customer support. AI tackles these chores rapidly and accurately, reducing operational costs and increasing output. 

For instance, a large retailer like Walmart employs AI-powered robots for inventory management. These robots scan store shelves, track product stock, and alert employees when items need replenishing. This diminishes workers' time on mundane tasks like manual inventory checks, enabling them to concentrate on more customer-facing roles, improving efficiency and cutting costs. 

Discreet Decision-Making

Manually analyzing data takes forever. But AI can sift through vast amounts of data in real time, revealing insights that shape intelligent decisions. 

With AI, businesses can foresee market trends, gauge customer preferences, and identify operational issues. These insights let companies respond swiftly to market shifts, staying competitive and fostering growth. 

For example, a financial firm such as JP Morgan uses AI algorithms to analyze real-time market data. The AI identifies market trends, potential risks, and investment opportunities. The system allows the firm to adjust portfolios quickly, capitalize on market opportunities, and make data-driven decisions with minimal human intervention, keeping it competitive in a fast-paced industry. 

Improved Customer Experiences

Personalization is the secret sauce to winning loyal customers today. AI enables companies to deliver highly personalized experiences, strengthening customer and company relationships. Tools like recommendation engines, chatbots, and sentiment analysis make products feel tailored. 

Businesses can explore customer behavior and preferences to tweak products, services, and marketing messages to fit individual tastes. This all adds up to a better customer experience. 

For example, streaming services like Netflix use AI to create personalized recommendations based on a user’s viewing history, preferences, and even the time they usually watch shows. This customization keeps users engaged, increases customer satisfaction, and helps the company retain subscribers by offering content tailored to individual tastes. 

Better Operations and Resource Handling

Artificial Intelligence touches many parts of business operations, like supply chain management and workforce scheduling. It analyzes both historical data and real-time variables for sharper insights. AI algorithms can fine-tune inventory levels, route planning, and production schedules. 

This means less waste and more efficiency. AI systems can dynamically allocate resources based on demand, ensuring optimal use and cost-effectiveness. 

For instance, Amazon uses AI for its supply chain management. AI forecasts demand based on historical data and external factors such as weather and customer behavior. This allows Amazon to adjust stock levels dynamically, improving inventory management, reducing waste, and optimizing warehouse operations. 

Proactive Risk Management and Security

Risk management is like the unsung hero of the business world. It can seriously make or break a company. And guess what? AI boosts the ability to identify and mitigate risks. 

It’s like having a trusty sidekick by your side, you know? Now, let’s talk about AI fraud detection systems. They’re like Sherlock Holmes in financial transactions, sniffing out suspicious activities left, right, and center. And those cybersecurity tools? They’re like the bouncers at a club defending against threats in real-time, no questions asked! 

Faster Innovation

Look at the mobile phone industry: only a few companies dominate because they constantly innovate. AI opens new doors for product development and optimization. Techniques like machine learning, natural language processing, and computer vision help businesses create cutting-edge products and services. 

New products must meet evolving customer needs, right? AI tools enable rapid prototyping, testing, and iteration. It’s like having a warp-speed button for product innovation, helping businesses bring products to market and stay ahead of competitors. 

For example, Tesla uses AI in its product development, particularly for its self-driving technology. Using AI-based systems for rapid testing and iteration, Tesla quickly improves its autonomous driving features, staying ahead of competitors and constantly bringing innovative products to the market. 

Scalability and Flexibility 

AI solutions are all about scalability and flexibility. They help businesses adapt to changing needs and grow smoothly. Whether handling a flood of customer inquiries or crunching massive amounts of data, AI has your back. 

These systems can scale up or down on the fly to meet demand. And with cloud-based AI platforms, scalability gets even better. They offer instant access to computing power and no need for pricey infrastructure. 

For example, customer service platforms like Zendesk integrate AI-powered chatbots that can scale to handle thousands of customer queries at once. During high-demand periods, such as holiday sales, AI systems can ramp up operations without requiring additional staff, maintaining high service levels even when customer inquiries surge. 

Stay Ahead in the Competition 

AI isn’t just a tool; it’s a competitive advantage. It lets businesses shine through top-notch customer experiences, groundbreaking products, or smooth operations. Being an early adopter of AI can put you at the top of the pack. 

Just be sure that if you’re not integrating AI into your business, your competitors will eventually. So, being an early adopter gives you the sweet advantage you need to gain a foothold in the market. Along the way, you’ll attract customers, investors, and top talent who shape the future of your industry. 

For example, retail giant Zara has integrated AI into its design and supply chain processes, allowing it to spot fashion trends quickly and restock its stores. Using AI to streamline operations and anticipate market shifts, Zara stays ahead of competitors, maintaining its position as a fast-fashion leader. 

OpenSesame: The Fast Track to Reliable AI

OpenSesame offers innovative AI agent infrastructure software that grounds AI models in reality. Our platform reduces hallucinations, enhances reliability, and saves hours of manual checking. Key features include real-time hallucination reports, business data integration, multimodal AI expansion, and open-source frameworks. We provide ungrounded truth recognition, prompt template extraction, accuracy scoring, and a hallucination dashboard. OpenSesame allows businesses to confidently build trustworthy AI systems, offering real-time insights without latency for high-performing, reality-grounded AI solutions. Try our AI agent infrastructure management software for free today!

Related Reading

• Trustworthy AI
• AI Problems
• Contextual AI
• AI Decision Making

How Can AI Help My Business In 12 Practical Ways

1. Use OpenSesame.dev to Improve AI Models 

OpenSesame.dev is an innovative platform that sharpens AI models. Our software helps ground AI in reality, reducing hallucinations, enhancing accuracy, and saving hours of manual checking. Key features include real-time hallucination reports, business data integration, multimodal AI expansion, and open-source frameworks. We provide ungrounded truth recognition, prompt template extraction, accuracy scoring, and a hallucination dashboard. 

OpenSesame allows businesses to build trustworthy AI systems confidently. It offers real-time insights without latency for high-performing, reality-grounded AI solutions. Try our AI agent infrastructure management software for free today!

2. Accounting

AI is making its way into accounting tools to generate cash flow projections and categorize transactions for tax, payroll, and financial forecasting. This helps reduce input errors, catch duplicate or suspicious transactions, and identify opportunities to save money. 

Example

Xero and QuickBooks are popular accounting software solutions that use AI to automate tasks like cash flow projection, transaction categorization, and tax reporting. 

These platforms help businesses reduce errors, avoid duplicate transactions, and streamline their accounting processes. AI-driven categorization ensures that each transaction is correctly logged while the software identifies potential tax-saving opportunities or financial risks.

3. AI in Content Generation

Content creators increasingly use generative AI tools to save time and improve content generation. Tools like ChatGPT, Google Gemini, and Jasper enable users to input text prompts to quickly generate new drafts of written content such as outlines, emails, or blog posts. Midjourney, Stable Diffusion, and DALL-E create images based on text prompts. A survey of business-to-business (B2B) marketers conducted by Demand Spring found that as of 2024, 82% of organizations use AI for content creation. According to the survey, AI-powered tools help with topic suggestions, headline optimization, and initial draft generation. 

Example

BuzzFeed and The Washington Post use AI to generate content quickly and efficiently. BuzzFeed has used AI to create quizzes and write engaging articles, while The Washington Post uses its in-house AI, Heliograf, to report on live events such as elections and sports. These AI tools assist with automating draft writing topic suggestions, improving editorial speed, and enhancing productivity and content quality.

4. Customer Service and Support

AI has a powerful impact on customer service, enabling businesses to extend their support capabilities. Chatbots and callboys can increase the volume of customer inquiries companies can handle, freeing up time for customer service agents to focus on more complex cases or interactions. Many AI-enabled call centers and voice applications can also analyze caller sentiment and transcribe video and phone calls. 

Example

Bank of America uses an AI-powered virtual assistant named Erica to assist customers with everyday banking inquiries. Erica provides real-time assistance through chat, helping customers check their balances, track spending, and manage bills. Similarly, Zendesk uses AI chatbots to handle customer inquiries, which frees up human agents for more complex support issues.

5. Marketing

Marketing teams use artificial intelligence tools and machine learning algorithms to analyze data, identify customer trends and patterns, optimize marketing campaigns and strategies, and enhance the customer experience. In addition to improving marketing strategy results, AI can help team members save time by automating manual tasks. According to a 2024 survey of 1,800 marketers distributed by Marketing Artificial Intelligence Institute and Drift, 78% of respondents believe they will intelligently automate more than a quarter of their tasks in the next three years. Additionally, 45% believe more than half of their marketing tasks will be intelligently automated to some degree by AI three years from now. 

Example

Spotify uses AI to analyze user behavior, segment audiences, and offer personalized recommendations. By leveraging AI, Spotify tailors playlists and advertisements to users’ preferences, significantly improving user engagement. HubSpot also uses AI for predictive analytics in marketing campaigns, helping businesses optimize their strategies and target the right audiences with personalized content. 

Here are a few examples of how AI is used in marketing 

Improved audience segmentation and personalization. AI can simplify how marketers track, understand, and predict customer behaviors. Using AI tools, businesses can also create customer profiles by segmenting customers into different categories depending on their behaviors, preferences, and demographic indicators. 

Based on customer profiles, marketing teams can personalize messaging and communications to highlight products, services, or promotions most relevant to specific customer segments—predictive marketing analytics. Marketers can use predictive analytics to identify patterns and trends from historical and current customer data, enabling teams to predict which strategies or campaigns may be most effective more effectively. Predictive analytics help anticipate customer needs, optimize targeting, and identify upselling and cross-selling opportunities: enhanced market research and competitor analysis. 

Marketing teams and professionals spend significant time conducting marketing and competitor research. AI systems and tools like Crayon and AlphaSense have advanced capabilities to find, organize, and analyze relevant market data and competitive differentiators, saving time that would have been spent on manual research. Because AI can process large amounts of data automatically, important market or competitor insights may be uncovered that marketing team members may have missed.

6. Cybersecurity

AI-powered cybersecurity tools can monitor systems activity and safeguard against cyberattacks, identifying risks and areas of vulnerability. It can also help security teams analyze risk and expedite their threat responses. 

Example

Darktrace, an AI cybersecurity firm, uses machine learning to monitor networks for unusual behavior, flag potential cyberattacks, and respond to threats in real-time. Darktrace’s AI adapts to new threats without manual intervention, enabling businesses to defend themselves against evolving cyberattacks efficiently.

7. Sales

Predictive analytics and AI-powered algorithms enable sales teams to understand customer behavior and preferences better and automate and improve sales operations. Salesforce released insights featuring 5,500 sales professionals across 27 countries and found that sales teams are reaping the benefits of AI. The latest edition of the annual State of Sales report found that 41% of sales organizations have the technology fully implemented in their operations, while another 40% are experimenting with AI. The report also found that 83% of sales teams with AI tools in place saw revenue growth in the past year, compared to 66% without AI. Sales teams can use AI to help with the sales process and strategy aspects, such as automating manual tasks. Much of sales professionals’ time is spent on manual tasks such as data entry and sharing updates on their deals in the pipeline—rather than actual selling. 

AI tools can help automate time-consuming tasks so sales representatives can spend more time on core functions, such as demand forecasting. AI can help analyze past performance and current economic indicators to help sales teams forecast future demand. Analyzing customer data, interactions, and historical sales patterns using AI algorithms can help identify leads, prioritize prospects, identify next steps or actions to engage prospects, and optimize sales. They are writing and personalizing outbound email campaigns. 

Generative AI tools like ChatGPT can be used to draft outbound emails to customers and leads. Leveraging data from AI-powered lead scoring tools, sales team members can personalize outreach and share product recommendations based on an individual’s score, preferences, and behaviors: Lead generation and scoring. AI-powered lead generation and scoring tools like LeadIQ, smooth.AI, and Outreach include capabilities like machine learning algorithms to provide real-time updates to sales teams about prospects and leads. This technology helps generate leads and ensure lead scores are accurate and current. When a lead clicks on a link in an email, downloads a resource from the company website, or takes another action, the AI algorithm automatically updates the lead's score. 

Example

Salesforce has incorporated AI tools like Einstein AI to help sales teams automate tasks such as data entry, lead scoring, and personalized outreach. With Einstein AI, sales representatives can better understand customer behavior and receive suggestions for the next best actions based on predictive analytics, improving customer relationships and driving sales.

8. Information Technology (IT) Operations

The use of AI in informational technology (IT) operations is so widespread that a particular term for it was coined: AIOps. AI can streamline data and maintain IT infrastructure, automating tasks like performance monitoring, workload scheduling, and data backups. It offers IT professionals better insights into the root causes of anomalies and errors, allowing them to resolve system issues and anticipate future ones quickly. 

Example

Companies like IBM use AI-driven solutions for IT operations, commonly called AIOps. IBM Watson AIOps help manage data, monitor system performance, and automatically resolve IT issues. This reduces the need for manual troubleshooting and allows IT departments to focus on strategic projects while improving system uptime and reliability.

9. Human Resources

Leveraging AI throughout the employee lifecycle—including sourcing and recruiting candidates, onboarding, managing employee records, and developing existing team members—can help human resource teams drive efficiencies and keep talent engaged. 

Example

Unilever uses AI in recruitment, leveraging platforms like HireVue to analyze video interviews and assess candidate responses. AI algorithms can screen applicants based on facial expressions, tone, and keywords, ensuring that only the most qualified candidates are shortlisted. This reduces bias in hiring and speeds up the recruitment process. While human resources has been slower than some other business functions to incorporate AI into day-to-day operations, research shows AI adoption among HR teams is on the rise. 

A survey conducted by Gartner of 179 HR leaders found that as of January 2024, 38% of HR leaders were piloting, planning implementation, or had already implemented generative AI, an increase from 19% in June 2023. Some of the many use cases for AI in human resources include Writing content for recruitment materials. Recruitment and talent acquisition teams can use generative AI tools such as ChatGPT or Google Gemini to help draft copy for recruitment and hiring purposes, including job descriptions, interview questions, candidate outreach emails, and job offer letters. The tool will generate a suggested copy by providing the tool with a prompt featuring relevant details about the job and type of content. While additional information may need to be shared, and edits will likely be required to finalize recruitment materials, AI tools can save time compared to writing copy from scratch. 

They are automating candidate screening. Many applicant tracking systems (ATS) and recruiting tools like Workable, EVA, and Paradox include AI technology to screen candidates based on specific criteria and qualifications automatically. These systems often include the capability to send automated emails to candidates, letting them know how to move forward. This enables recruitment and talent acquisition teams to focus their time on core functions. They are driving candidate engagement. 

Some employers embrace customer service chatbots as an innovative solution to drive candidate engagement like customer service chatbots. Companies include AI chatbots and virtual assistants on their careers pages to direct individuals to jobs that align with their skills and experience, guide them through an interactive application process, and answer common questions—simplifying workforce planning. Talent management systems and human resources information systems (HRIS) such as Leena AI, Beamery, and Gloat centralize employee data, making it easier for companies to manage and automate HR processes. 

These systems allow organizations to manage payroll, benefits, time and attendance, learning and talent development, and other HR functions. Many of these systems also include data related to talent reviews, performance, engagement, retention, and skills, helping organizations better understand worker competencies, skills gaps, and future workforce needs.

10. Financial Analysis, Trading, and Fraud Detection

Financial departments and businesses can benefit from quick and powerful AI-driven data analysis and modeling, fraud detection algorithms, and automated compliance recording and auditing. Because of AI’s ability to analyze large, complex datasets, individual and institutional investors use AI tools to manage their portfolios. AI can also detect fraud by identifying unusual patterns and behaviors in transaction data. 

Example

JP Morgan uses its AI COiN (Contract Intelligence) to analyze legal documents and extract critical data points faster than human analysts. Similarly, PayPal employs AI for fraud detection, where machine learning algorithms detect suspicious transactions in real time, reducing financial losses and enhancing security.

11. Legal Department

Corporate legal departments process and analyze large volumes of data and documents. Rather than manually reviewing documents and completing other administrative processes, AI can simplify many legal tasks, enabling lawyers to spend more time providing clients with expert guidance. Litify research featuring insights from legal professionals found that AI adoption among respondents doubled from 2023 to 2024, reaching 47%, and is projected to reach 60% by 2025. The research also found that 92% of respondents using AI are saving time on legal work—with 33% now saving up to 10 hours per week. 

Here are some specific ways AI can be used in legal departments: Research and analysis. Legal research involves reviewing legal cases, laws, regulations, precedents, and other information. AI-powered tools and platforms like CoCounsel, Paxton, and Callidus can automatically retrieve, organize, and analyze relevant legal documents. This simplifies the process of legal professionals finding critical information, helping them to extract key insights and make informed decisions more quickly. Contract review and due diligence. Reviewing legal contracts and documents can be time-consuming and prone to human error. 

In addition to being reviewed by human legal experts, AI tools with machine learning capabilities can review and analyze contract language to flag potential issues or unfavorable terms that may be overlooked. Compliance. Different industries and businesses must comply with specific regulations, such as HIPAA for U.S. healthcare data and GDPR for businesses that collect data from European Union Citizens. Compliance standards are complex, and maintaining compliance can lead to breaches or penalties. Companies can leverage and train AI algorithms to understand specific laws and regulations more efficiently and identify discrepancies than manual methods.

 Document automation. AI tools such as Gavel, Clio Draft, and Briefpoint can help generate initial drafts of standard legal documents, such as contracts, nondisclosure agreements (NDAs), wills, and leases, saving legal teams time and reducing human error. Remember that while AI can create drafted legal documents, a thorough review by a legal professional is critical before using any AI-generated documents. Example: Law firms like Littler Mendelson have adopted AI tools like Kira Systems to help with contract review and due diligence. Kira’s AI scans legal documents for specific clauses, inconsistencies, and risks, allowing lawyers to focus on high-level legal strategy while saving time on administrative tasks. The AI-driven review process enhances accuracy and efficiency, especially during mergers and acquisitions.

12. Supply Chain and Logistics

AI can significantly impact operations, whether as a forecasting or inventory management tool or an automation source for manual tasks like picking and sorting in warehouses. It can help allocate resources or people, like drivers, schedule processes, and solve or plan around operational disruptions. 

Example

UPS uses AI to optimize its delivery routes, saving time and reducing fuel consumption. Its AI platform, ORION (On-Road Integrated Optimization and Navigation), uses real-time data to adjust delivery schedules and routes based on traffic, weather, and customer preferences. AI also powers Amazon's warehouse operations, where robots assist with picking and sorting packages, increasing efficiency and accuracy in order fulfillment.

How To Build A Successful AI Strategy In Your Business

Use OpenSesame

OpenSesame is a key player in helping businesses successfully implement AI. OpenSesame provides innovative AI agent infrastructure software that grounds AI models in reality. Our platform helps to reduce hallucinations, enhances reliability, and saves hours of manual checking. Key features include real-time hallucination reports, business data integration, multimodal AI expansion, and open-source frameworks. 

We provide ungrounded truth recognition, prompt template extraction, accuracy scoring, and a hallucination dashboard. OpenSesame allows businesses to confidently build trustworthy AI systems, offering real-time insights without latency for high-performing, reality-grounded AI solutions. Try our AI agent infrastructure management software for free today!

Understand Available AI Technologies

Begin by learning about the various AI technologies available today. This includes generative AI, machine learning, natural language processing, and computer vision. Research how these AI technologies are applied in different industries to identify use cases relevant to your business. List specific issues AI can address and the benefits to be gained. Note the departments that use it, their methods, and any potential roadblocks.

Assess Your Business

Next, understand your organization, its priorities, and its capabilities. Review the size and strength of the IT department, which will implement and manage AI systems. Interview department heads to identify potential issues AI could help solve.

Define Clear Objectives

What problems does your organization need to solve? What metrics need improvement? Don’t assume AI is always the answer. Choose business objectives that are important for the business and that AI has a track record of successfully addressing.

Identify Partners and Vendors

Find companies in the AI and machine learning space that have worked within your industry. Create a list of potential tools, vendors, and partnerships, evaluating their experience, reputation, pricing, etc. Prioritize procurement based on the phases and timeline of the AI integration project.

Build a Roadmap

Create a roadmap that prioritizes early successes that will bring value to the business. Choose projects based on identified practical needs. Determine the tools and support needed and organize them based on what’s most crucial for the project, specifically:

Data

Develop a data strategy by determining whether new or existing data or datasets will be required to fuel the AI solution effectively. Establish a data governance framework to manage data effectively.

Algorithms

Algorithms are the rules or instructions that enable machines to learn, analyze data, and make decisions. A model represents what a machine learning algorithm learned. Determine who will deploy algorithms and design, develop, and validate models, as expertise is needed to manage these tasks effectively.

Infrastructure

Determine where your AI systems will be hosted and how they will be scaled. Consider whether to deploy on your infrastructure or third-party platforms.

Talent and outsourcing

Assess the readiness and skills gaps within the organization to implement AI initiatives. Determine if a talent pipeline exists to fill roles such as data scientists and developers or if skills can be developed internally through training. Also, assess if certain tasks, such as deployment and operations, should be outsourced.

Present the AI Strategy

Present the AI strategy to stakeholders, ensuring it aligns with business objectives. Attain buy-in for the proposed roadmap. Communicate the benefits, costs, and expected results. Secure the necessary budget to implement the strategy.

Begin Training and Encourage Learning

Start upskilling AI teams or hiring individuals with the right AI expertise. Encourage teams to stay updated on cutting-edge AI advancements and to explore innovative problem-solving methods.

Establish Ethical Guidelines

Understand the ethical implications of the organization’s responsible use of AI. Commit to ethical AI initiatives, inclusive governance models, and actionable guidelines. Regularly monitor AI models for potential biases and implement fairness and transparency practices to address moral concerns.

Assess and Adapt

Keep up with the fast-paced developments of new products and AI technologies. Adapt the organization’s AI strategy based on new insights and emerging opportunities.

Challenges of Using AI In Businesses (+Solutions)

1. The Skills Gap: No One at the Office Knows AI Like That Guy on YouTube.

A major AI implementation hurdle is the need for in-house expertise. To overcome it, invest in training, collaborate with experts, hire AI talent, start small with pilot projects, and use user-friendly AI tools. Building internal expertise is key to successful AI adoption. - Nic DeAngelo, Saint Investment - Real Estate Funds

2. Where Do We Start With AI?

One of the biggest hurdles—with one of the most significant potential downsides when executed incorrectly—is deciding where to implement AI. While it might be tempting to say, "Let's add that chatbot for website inquiries," or "Let's stuff our blog with AI-generated articles," AI should not be used anywhere that it will negatively impact the overall customer experience. 

In almost every instance, AI should help alleviate tasks from an employee closely monitoring AI rather than being released to replace a role. Customers who get frustrated by wrong information or bad experiences (stemming from AI or otherwise) may move on and find a solution with a competitor before you even have a chance to salvage the sale. - Brittany Hodak, Creating Superfans

3. Outdated Systems Can’t Support AI Technology.

One hurdle businesses face when implementing AI is the need for updated infrastructure with processing capabilities that can handle large amounts of data in minimal time. Most companies struggle with outdated systems, tools, and applications, making AI integration difficult. Whether it is the proper storage, processors, or the necessary training needed to understand these new tools and troubleshoot problems, businesses should find the right AI provider or vendor who has the requisite AI experience, expertise, and certifications to help carve a manageable cost component and guarantee a smoother transition to AI implementation. - Brian David Crane, Spread Great Ideas

4. Data Privacy And Security Concerns Of AI Implementation

Data privacy and security concerns are among the biggest challenges businesses face with AI. AI models typically require large data sets to learn and generate high-quality outputs. However, handling sensitive information poses serious risks. Businesses must ensure compliance with data protection regulations and safeguard sensitive data from potential breaches. 

This will require companies to stay on top of the latest AI and data protection trends to ensure they’re up to speed with changes. The risks of AI systems and threats of malicious use will likely be a big challenge for years. - Blair Thomas, eMerchantBroker

5. Intellectual Property Issues With AI

The biggest hurdle is the challenge around intellectual property (IP). It is difficult to determine the ownership and inventorship of AI-generated or AI-assisted outputs when using AI, especially when multiple human and machine agents are involved. So, businesses must navigate the risk of infringement or misappropriation of IP rights by unauthorized or malicious use of AI systems, such as copying, reverse engineering, or hacking. - Renato Agrella, Acerca Consulting

6. Lack Of Personalization With AI Solutions

One of the hurdles businesses face when implementing AI is the inability to create personalized solutions by default. AI facilitates different processes; however, companies can only partially rely on AI-powered tools to automate various processes. 

Whichever solutions you devise with the help of AI lack a human touch, and to make up for it, you have to be actively involved in the process to get the result that meets your preferences. Businesses can partially overcome this challenge by training artificial intelligence systems. But in the end, AI and humans need to join forces to develop solutions best suited to their needs or preferences. - Stephanie Wells, Formidable Forms

7. Large Language Models Are Tricky to Use

A significant challenge for businesses implementing AI lies in effectively utilizing large language models (LLMs) to produce high-quality, engaging, SEO-friendly content. While tools like ChatGPT offer value, the crucial factor is finding the optimal equilibrium between AI and human expertise. More reliance on AI can result in subpar content, plagiarism risks, and diminished search engine rankings due to excessive duplication. 

On the other hand, neglecting AI tools means forgoing efficiency gains that can set businesses apart and attract customers, potentially affecting competitiveness and expansion. To address this challenge, assess your processes carefully and determine the ideal balance at each stage to meet your objectives effectively. - Kevin Getch, Webfor

8. Too Many AI Tools Create Confusion

One of the most common hurdles is technological overwhelm. Many businesses add too many tools without analyzing how they will use them, resulting in three different content generation platforms. 

They pay for all the subscriptions, but their teams don't use them. This inefficiency can be easily avoided if you decide which tool to purchase based on its utility for your workflows rather than its significant promise and shiny cover. - Solomon Thimothy, OneIMS

9. Customers Are Wary Of AI

They are gaining customer acceptance. While AI can bring many benefits, like improved efficiency and personalized experiences, some customers still have reservations. They worry about their data privacy, fear job losses, or don't trust AI to make decisions. To tackle this, businesses need to be transparent about how they use AI, emphasizing data security and showing how it can complement human expertise rather than replace it. 

Businesses must also involve customers in the AI journey. Building trust takes time, so continuous communication and education about AI's advantages are essential. Ultimately, it's about demonstrating that AI can enhance the customer experience, not compromise it. - Abhijeet Kaldate, Astra WordPress Theme

10. There Are Too Many AI Options

There are too many options. It takes time to figure out where to start. First and foremost, identify your specific business goals and challenges. Determine where AI can make the most impact. Additionally, AI analyzes customer needs and pain points. AI tools can enhance the customer experience and address some of these pain points. Study what your competitors are doing with AI as a reference, too. 

Verify if it would also be helpful for your business. It is essential to consider your budget, as many options are available these days. Start with the most impactful solutions, test and evaluate, iterate this process, and expand as your business grows. - Meeky Hwang, Ndevr, Inc.

Related Reading

• Challenges of AI
• Model Evaluation Metrics
• Unpredictable AI
• How to Reduce Bias in AI

Try Our AI Agent Infrastructure Management Software for Free Today

OpenSesame offers innovative AI agent infrastructure software that grounds AI models in reality. Our platform reduces hallucinations, enhances reliability, and saves hours of manual checking. Key features include real-time hallucination reports, business data integration, multimodal AI expansion, and open-source frameworks. 

We provide ungrounded truth recognition, prompt template extraction, accuracy scoring, and a hallucination dashboard. OpenSesame allows businesses to confidently build trustworthy AI systems, offering real-time insights without latency for high-performing, reality-grounded AI solutions. Try our AI agent infrastructure management software for free today!

Related Reading

• How to Improve Machine Learning Model
• AI Decision Making Examples
• How to Build an AI agent
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• AI Agent Frameworks