Tag: AI Software Product Development

Why Use Embedded AI In My Business Apps and Products?

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May 27, 2026

The Use of Embedded AI in Apps and Software Products

It is hard to miss the relevance of artificial intelligence (AI) in our society today. Discussions about its impact on our day-to-day lives, on technology and on competitive markets appear in the media, in industry publications and in kitchen table conversations.

When it comes to the use of Embedded AI within existing and new applications and software products, the discussion is no less active or relevant.

The University of Cincinnati recently reported that AI could contribute $15.7 trillion USD to the global economy by 2030. The integration of that technology into existing and new software products, applications and websites can, and should, be a part of any competitive strategy where business users or consumers and end users use technology to buy, communicate, gather information, etc.

The use of embedded AI within software products, apps and websites can:

  • Streamline development time and deliver new features and functionality to keep pace with the market and customer needs
  • Provide innovation within existing or new products to enhance competitive advantage
  • Enhance and improve customer and user satisfaction with quick, responsive features that provide detailed information, targeted to user needs
  • Improve productivity within business teams by providing automated workflow and processes to complete inquiries, approvals, etc. with limited or no human intervention

These are just a few of the advantages of Embedded AI.

Using Embedded AI to Upgrade and Improve Your Apps, Software Products and Competitive Advantage

TechTarget recently published a paper reporting on the findings of renowned research organizations and the global use of AI within businesses.

  • McKinsey & Co. – 88% of businesses report regular AI use in at least one business function (up from 78% in a prior year survey).
  • Gartner – Advantages of AI use within apps and the organization include incremental improvements to existing processes and workflows, modified processes that accelerate growth and profitability and altering business models to transform the business in ways that will redefine the market.

Can Agentic AI Help My Business, and How Will it Impact My Staff?

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January 28, 2026

Agentic AI Can Be Used to Support Business and Teams

A recent study by Deloitte Reports that 52% of respondents say that Agentic AI is the most interesting area of artificial intelligence today.

Agentic AI takes artificial intelligence to the next level by enabling decision-making and independent behavior that involves reasoning, planning and completing tasks and actions in real time to achieve established goals.

Thirty years ago, we could not have imagined this technology, nor the impact it would have on productivity, work processes, businesses and consumers. In this rapidly evolving environment, it is worth considering the impact on jobs and on the people who previously performed the tasks we now as AI to complete.

Let’s consider some of the uses of Agentic AI so that we can better understand its potential and how it can be (and is) used in today’s business environment and how the use of Agentic AI will impact those currently working in each of these environments.

How Can Businesses Use Agentic AI to Help the Business and Support Team Members?

Manufacturing

Use Case: The typical manufacturing environment is supported by numerous systems, functions and processes. To complete the cycle, the business must incorporate the supply chain for parts and components and manage a multi-step, multi-level workflow. Agentic AI can work independently to identify supply shortages and review alternative sources for supplies that meet requirements for the timing of shipping and the price of materials. It can complete and submit forms and manage production schedules to accommodate the arrival of materials and meet deadlines.

Staffing Impact: If the business intends to engage Agentic AI to perform these tasks, it would be wise to include team members in the process to control specific, critical points along the manufacturing lifecycle and to monitor and manage the process to ensure appropriate decisions and action.

Call Centers

Use Case: Agentic AI is in use today in many call centers. AI agents gather and use existing intelligence to address and serve customers, considering order history and customer preferences, customer satisfaction, and company policies for returns, shipping and other factors.

Staffing Impact: Agentic AI can relieve live agents from the more mundane tasks and, when a live agent interacts with a customer, that agent can quickly leverage information gathered from previous interactions and orders and even suggest solutions and purchases or alternatives based on the information gathered by the AI assistant.

Healthcare

Use Case: Human interaction is crucial to healthcare but Agentic AI can help with the more routine activities like scheduling appointments, processing insurance claims and aligning government and industry regulations with tasks performed to ensure compliance. The system can review electronic health records (EHR) to bring together unstructured notes into a summary and provide classification information.

Staffing Impact: By streamlining the routine tasks, note-taking and summarization, Agentic AI can enable staff optimization and allow healthcare professionals to focus on patient interaction, records review and diagnostics and other crucial activities.

Research and Compounding

Use Case: Whether a business is developing a pharmaceutical compound or creating a food recipe, this process can take a lot of time and involve a lot of trial and error. Agentic AI allows the business to consider other additives, ingredients and compounds, compare the pricing for these new ingredients and compounds and the manufacturing requirements, alternatives and possible issues.

Staffing Impact: Skilled team members can use the information gathered and recommended by Agentic AI to review results, and make alternative recommendations or test theories and make final decisions.

As Artificial Intelligence (AI) evolves, it is important for businesses to weigh the experience, skills and knowledge of its team members and to incorporate those factors into the decisions surrounding the use of AI. Agentic AI and other technologies can be very helpful in performing routine activities, redundant tasks and even some decisions. But human intervention and experience are always important to identify and address the more nuanced issues and bring a trained eye to the final product, service or decision.

AI is at its best when it is used to its full potential, in concert with the human element of skills, experience and knowledge and it can be a benefit to your team by relieving them of routine tasks and by revealing interesting ideas and concepts that can be refined and used to create new business products and services and solving problems.

Contact Us to find out more about how your business can incorporate Artificial Intelligence (AI), natural language processing (NLP) and machine learning into your products, your business processes and your Digital Transformation (Dx) initiatives. Our Products And Services can help you achieve your vision with affordable, dependable technology. Explore our free articles about Agentic AI: ‘The New Age Of AI: Agentic AI’, and ‘What Is Agentic AI And Why Should I Consider It For Apps?’

Original Post: Can Agentic AI Help My Business, and How Will it Impact My Staff?

AI-Infused Apps and Products Provide Improvement Across the Enterprise

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January 12, 2026

Why Infuse New or Existing Software with Artificial Intelligence?

Artificial Intelligence (AI) has been in the mainstream for years with new advancements occurring every day. As the promise of AI evolves, businesses are undertaking new AI software development projects to support consumer products and internal business processes, and many companies are infusing AI into existing software products and apps to modernize and upgrade features and functionality, scalability and the quality of system interaction with human users.

Gartner predicts that by 2026, around a third (30%) of new applications will leverage AI.

‘By leveraging AI, businesses can tap into its numerous benefits and advantages, positioning themselves for continual success and growth.’

On the back-end, the benefits of AI development include improved speed of development and time to market. According to McKinsey research, Generative AI Accelerates Certain Coding Tasks By 35% To 45%.

Infusing AI allows you to incorporate the advantages and advanced technologies of the AI landscape into the enterprise to automate, predict and optimize and to improve business decisions and outcomes, as well as improve user adoption of intuitive tools and features.

Infusing AI into the environment also allows you to more quickly adapt and upgrade to accommodate changes to customer needs, business user needs and the competitive market. Development can be completed quickly and new, more sophisticated features can be added on a shorter cycle. You can develop faster and design and deliver software and applications to create dynamic end-user experiences.

There are real business benefits to adding AI into the mix! The data gathered and delivered by AI can provide real-time results. For example, a decision regarding loan approval should be based on currently available information and the transaction should be approved or denied using the most up-to-date information in order to protect the interests of the prospective client and the business. Interest rates and other variables can be calculated to provide the best outcomes. The system can detect and protect against fraud to ensure that insurance claims are valid and appropriate.

By infusing existing systems with artificial intelligence or building new systems to incorporate these capabilities, the business can mitigate risk, speed business processes and approvals and automate many redundant tasks, thereby improving team productivity, customer satisfaction and competitive advantage in the market.

Does an AI-Infused App or Software Product Benefit a Business and Its Customers?

By leveraging AI, businesses can tap into its numerous benefits and advantages, positioning themselves for continual success and growth. Benefits of AI-infused technologies include:

Competitive Advantage – Businesses can secure an edge over their competitors through the use of AI technologies that amplify productivity, decision-making processes, and consumer experiences.

Personalized User Experience – AI technology allows businesses to effortlessly examine consumer behavior and preferences, enabling the provision of products, recommendations, and services tailored to their precise needs.

Data-Driven Insights – AI-based solutions help businesses forecast business trends, identify patterns, and make informed decisions by analyzing vast amounts of data and extracting invaluable insights, paving the way for better planning.

Operational Efficiency – By automating repetitive tasks, streamlining workflows, and optimizing resource allocation, AI-driven software helps businesses simplify their operations, improve productivity, and reduce costs.

‘Infusing AI allows you to incorporate the advantages and advanced technologies of the AI landscape into the enterprise to automate, predict and optimize and to improve business decisions and outcomes, as well as improve user adoption of intuitive tools and features.’

Contact Us to find out how our Enterprise Software Services and Artificial Intelligence Development Services can support your business needs and ensure consistent, professional, skilled technology and knowledge. Explore our free White Paper: ‘What Is Artificial Intelligence Technology And How Can It Help My Business?’

Original Post: AI-Infused Apps and Products Provide Improvement Across the Enterprise!

Case Study: Elegant MicroWeb Case Study – AI Image Recognition Technology Transforms Fire Safety Inspections and Compliance

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December 22, 2025

This U.S. company specializes in fire safety equipment maintenance and compliance management. Its mobile application product automates the process of fire safety inspections, allowing businesses to efficiently record and submit inspection reports to regulatory authorities, streamlining inspection workflows and ensuring consistent compliance for clients. This product is accessed through a subscription plan.

Continue reading “Case Study: Elegant MicroWeb Case Study – AI Image Recognition Technology Transforms Fire Safety Inspections and Compliance”

The New Age of Artificial Intelligence: Agentic AI

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August 13, 2025

Agentic AI Optimizes Resources and Productivity

For the last several years, the buzz in the technology domain and in the consumer market has been about Artificial Intelligence (AI). AI is everywhere and it is impossible to avoid it

One of the more recent developments in this arena is Agentic Artificial Intelligence. Agentic AI takes AI to the next level with systems that can make decisions without human intervention.

Gartner predicts that ‘Agentic AI will introduce a goal-driven digital workforce that autonomously makes plans and takes actions – an extension of the workforce that doesn’t need vacations or other benefits.’ That’s quite a bold prediction and, if true, it will have a profound effect on the way businesses operate and how team members do their jobs.

‘Today, Agentic AI is used to manage many functions and to make decisions without team member assistance.’

Most businesses today are considering how to incorporate artificial intelligence (AI) into their consumer apps, business applications, websites and mobile applications, or they have already begun to make these changes.

With the advent of Agentic AI, businesses can move more quickly to achieve goals and they can enhance productivity with intelligent solutions that target demographics and specific customer groups, improve technology and resource optimization, create content without human intervention and leverage systems that make autonomous decisions to complete tasks.

The Many Advantages of Agentic AI for Businesses, Team Members and Consumers

The primary advantages of Agentic AI are:

  • Integration with Systems – Agentic AI can easily integration with customer relationship management (CRM) and Enterprise Resource Planning (ERP) systems to enhance and execute components of workflow
  • Problem Solving – Agentic AI can take in and adapt to new information to solve problems and complete multi-step tasks, using sophisticated reasoning and iterative planning features.
  • Decision-Making – Agentic AI can make decisions without human intervention.
  • Operates Outside Machine Learning (ML) Environment – Agentic AI goes beyond classic AI-trained models to achieve true process automation.

Today, Agentic AI is used to manage many functions and to make decisions without team member assistance. Here are just a few of the Agentic AI applications a business might consider:

  • Virtual Assistants and Schedule Management
  • Traffic Navigation for Autonomous Vehicles
  • Supply Chain, Inventory and Logistics Management
  • Travel Including Flight Scheduling, Lodging and Tour Scheduling
  • Data, System and Cybersecurity with Threat Monitoring and Incident Reporting
  • Report Creation Incorporating Multi-Media, Multiple Reports and Summaries
  • Help Desk Activities to Record Issues, Suggest Solutions and Escalate to Live Agents
  • Manufacturing Including Machine, Component and Physical Asset, Scheduled Outages, Maintenance, Alerts etc.
  • Research Analysis Incorporating Articles, Data, and Models
  • Data Analytics and Data Management to Analyze Data and Generate Insights and Reports in Real-Time
  • Content Creation for Targeted Marketing and Advertising Including Automated Tasks, Tracking Performance Monitoring Spending
  • Customer Service Including Inquiry Handling, Issue Resolution and Follow-Up
  • Technology and Software Development to Analyze, Write, and Fix Code

‘With the advent of Agentic AI, businesses can move more quickly to achieve goals and they can enhance productivity and optimize resources with intelligent solutions that target demographics and specific customer groups, improve technology and resource optimization, create content without human intervention and leverage systems that make autonomous decisions to complete tasks.’

There are many more applications within the realm of Agentic AI possibilities, but this list will give you some ideas to get you started with your own business brainstorming activity.

When you employ expert assistance from a skilled IT partner, your enterprise can leverage Agentic AI And Other Components And Technologies within the Artificial Intelligence (AI) market to gather, produce and analyze information from disparate data sources, and use that data to create products, enhance services, improve productivity and improve market position. Engage a team that is skilled in AI, Data Science, Data Engineering and Predictive Analytics.

Contact Us to find out how Agentic AI and other AI technologies and services can support your software applications, mobile application, or software product ideas, and improve team productivity, optimize resources and advance Digital Transformation (Dx). Read our free blog article: ‘What Is Agentic AI And Why Should I Consider It For Apps?’

Original Post: The New Age of Artificial Intelligence: Agentic AI!

What is MCP and Why is it Important to My Business?

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July 30, 2025

How Does MCP Help AI Application Development?

Technology is great! But it can be hard to keep up. Even if you have made a career in technology, the pace of change today is so rapid that, if you miss one issue of your favorite tech publication, you may risk falling behind.

Perhaps nothing has increased the pace of change in technology more than Artificial Intelligence (AI) and, because AI potential seems to be unconstrained, the need for expanded capabilities and foundations is constant.

One such development is Model Context Protocol (MCP). MCP is an open protocol that was created by Anthropic to simplify the process of interacting with Large Language Models (LLMs) and to standardize the way in which applications provide context to LLMs and help them interpret data.

It may help to think of MCP as a translator or a way to make connections. Much like a USB adapter can connect an external hard drive to your laptop, MCP can connect various tools and data sources to enable interaction, integration and context for use in AI.

While early stage AI struggled to connect disparate data sources, tools and Application Programming Interfaces (APIs), the advent of Model Context Protocol (MCP) provides a bridge to external data and services to connect AI models using a standardized communication framework to allow for AI reasoning and processing. So, AI models like Azure OpenAI, GPT, Atlassian and others can fetch data, connect and interact with APIs and perform tasks, going well beyond the knowledge contained in the model to produce new, expanded outputs.

What is Model Context Protocol (MCP) and WHY Should I Care?

In the good old days of AI (just last year), your users might ask a complex question or a question that exceeded the information contained within an LLM training data set. That question could elicit an answer that made no sense or the system might simply frustrate the user by saying, ‘I don’t know.’ In order to solve that problem, you would have to provide data refinement to ensure that the LLM had context or you would have to add another tool or secondary source. That can be complex, time consuming and expensive.

In short, in order to succeed with your LLM, you were constrained by the amount of training data, and how well you could anticipate what your clients or users would ask or need. Sure, the information exists out there somewhere, but your LLM doesn’t include that data! You could use APIs but that process of application integration is complex and can be difficult to implement in a meaningful way, and you have to hard-code each connection! Using this technique to provide information to an LLM requires you to review documentation and data, identify the end point of the search, verify authentication, structure requests and then make sure it all works seamlessly so your users are not frustrated.

MCP allows you to create a bridge between apps and tools and establish automated workflows, using the power of LLMs to perform tasks and provide clear, concise information across all technology frameworks and platforms. MCP allows developers and content managers to establish what the LLM should know and provide that in a standard format that the LLM can understand. In essence, MCP acts as the go-between or the middleman, simplifying the relationship and connection between the LLM and APIs, tools and data repositories. Rather than your app reaching out to the API, it communicates with an MCP server. The MCP server will then translate that information and decide how to communicate with the API to satisfy the user request. It’s a translator!

Model Context Protocols (MCP) provide support for application developers using AI so they can more easily build apps and integrate information, ensuring that the app is flexible enough to support future integration of tools and data. Its open-source accessibility allows software developers and software vendors to leverage these tools to create business and consumer apps.

The team can create apps that are extensible at runtime and connect tools and APIs to an MCP server, to use the app immediately without extensive coding and deployment. The process is simple.

  • When a user enters a query, the Large Language Model (LLM) sends a request to the MCP server
  • The MCP server translates the request and decides where it should go (API, tool, etc.), and then sends it to the appropriate source
  • The response to the query is returned through the MCP server
  • The MCP server sends that response to the LLM
  • The user receives the response

It’s just that simple.

If you, your IT staff, your management team or your customers are asking about the potential of AI and LLMs, it is time to consider MCP and how it can support your needs. The incorporation of this approach can save development time and expense and alleviate rework and developer and user frustration.

If your business wishes to improve productivity, timelines, budgets and dependability of in-house applications, you will want to find a vendor and service provider who appropriately employs AI and LLMs to support its development model. If you are planning to engage an IT expert to augment your own software product or solution, it is wise to look for this capability when you interview prospective partners. Contact Us to find out how to integrate AI And LLM capabilities into your software project, website, analytics initiative or other project. Explore our free White Papers: ‘What Is AI And How Can It Help My Business,’ and ‘The Practical Use Of GenAI In BI And Analytics Tools.’

Original Post: What is MCP and Why is it Important to My Business?

Why Include AI In Your Upcoming Software Development Project?

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July 1, 2025

Should I Include AI In My Software Development Strategy?

Whether you are a business owner, a business manager, a team member or a consumer, the chances are good you have read articles and seen media coverage of the influence of AI. There is no doubt that Artificial Intelligence (AI) has already had a profound impact on business, everyday life and our perception of what technology can do.

A recent study by Forbes revealed that:

Breathe Life Into Your Business and Consumer Products with AI Features

  • 64% of businesses expect AI to increase productivity
  • 72% of businesses have adopted AI for at least one business function
  • Healthcare and automotive industries are expected to see the most impact from AI use
  • Over 60% of business owners believe AI will improve customer relationships

‘AI is evolving rapidly and it will continue to do so. It provides significant potential and it can serve your business today with customer-facing and internal applications, software and products that will provide a competitive edge and improve your productivity, market reach and customer satisfaction.’

If your business is considering AI as part of your technology strategy, you may be stalled in the process because you are unsure. Business concerns often include:

  • Is AI capable of meeting my business requirements?
  • Will AI be flexible enough to accommodate future requirements?
  • Will AI development be expensive and complex?
  • Can AI truly take my development project to the next level?

By leveraging AI, businesses can tap into its numerous benefits and advantages, positioning themselves for continual success and growth. Here are a few reasons why an endeavor into AI development must be considered:

  • Competitive Advantage – Businesses can secure an edge over their competitors through the use of AI technologies that amplify productivity, decision-making processes, and consumer experiences.
  • Personalized User Experience –  AI technology allows businesses to effortlessly examine consumer behavior and preferences, enabling the provision of products, recommendations, and services tailored to their precise needs.
  • Data-Driven Insights – AI-based solutions help businesses forecast business trends, identify patterns, and make informed decisions by analyzing vast amounts of data and extracting invaluable insights, paving the way for better planning.
  • Operational Efficiency – By automating repetitive tasks, streamlining workflows, and optimizing resource allocation, AI-driven software helps businesses simplify their operations, improve productivity, and reduce costs.

If you are considering the use of Artificial Intelligence (AI) and you want to leverage its potential today, there are many ways to do so without overreach and risk. AI is evolving rapidly and it will continue to do so. It provides significant potential and it can serve your business today with customer-facing and internal applications, software and products that will provide a competitive edge and improve your productivity, market reach and customer satisfaction. With the right planning and integration, and the right Artificial Intelligence (AI) development partner, AI technology can serve your business and your customers and team with competitive products and services and tools that will improve workflow, customer satisfaction, and time-to-market.

‘By leveraging AI, businesses can tap into its numerous benefits and advantages, positioning themselves for continual success and growth.’

Explore our expert Artificial Intelligence Development services. Discover our Software Application And Maintenance Services, Software Application Development Services and ongoing technology support. Build Your Software Team using our resources, skills and experience. Explore the benefits of Artificial Intelligence (AI) development in our free White Paper: ‘What Is Artificial Intelligence Technology And How Can It Help My Business?,’ and ‘The Practical Use Of GenAI In Business Intelligence And Analytics Tools.’

Original Post: Why Include AI In Your Upcoming Software Development Project?

Look For a Software Development Partner That Uses AI and LLMs

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June 25, 2025

AI and LLMs Support Developer and DevOps Productivity

A recent Copilot study revealed an interesting fact about the use of AI and Large Language Models (LLM) in the software development process. The study included developers from Microsoft, Accenture, and a Fortune 100 electronics firm and reported a 26% boost in productivity, increasing output from the usual eight hour workday to what amounts to ten hours of traditional output. This improved output increased even more for less experienced developers.

By leveraging Artificial Intelligence (AI) and Large Language Models (LLM), the DevOPS organization can greatly improve output, code quality, developer productivity and consistency. As businesses embrace the collaborative and team-oriented concepts of DevOps, the use of AI and LLMs can be utilized across the organization, and forward-thinking organizations are looking at the set of practices in DevOps (software development IT operations) to automate processes and accelerate the software development lifecycle.

Where software vendors employ these techniques, clients, customers and end-users can benefit from this approach. The development team can work more quickly and efficiently to satisfy requirements, design, develop and test and deploy, so business projects can be completed more rapidly and dependably.

If a business is considering a vendor or a software product for implementation within the walls of the enterprise, it is worth asking the prospective vendor and service provider how they are currently using cutting-edge technology to improve their development process and lifecycle.

Elements and Aspects of AI in Software Development

The Use of AI and Large Language Models (LLM) Improves the Development Process

Prompt Engineering uses natural language interfaces to study interactions with and the programing of LLM computation systems to enable complex problem solving, looking for patterns and focusing on reusable solutions. Infrastructure-as-Code (IaC), Code-as-Data and CodeQL LLMs support developers by exploring the code, studying requirements and documentation and analyzing infrastructure to find issues and inconsistencies.

Automated Code Generation allows the development team to optimize testing and deployment. Developers can use AI code review tools like Codiga and testing tools like DiffBlue Cover to review and analyze code and find issues, and AI-based code generators like GitHub and Copilot.

Generative AI (GenAI) leverages LLMs to streamline the steps in the development process, including analysis of requirements, coding and testing.

Natural Language Processing (NLP) enables code generation with machine learning and produces suggestions to develop or complete code, thereby reducing the occurrence of human error and allowing developers to focus on other, more complex aspects of code and development.

Testing and Debugging can be automated to detect and address bugs, inefficiencies and vulnerabilities in the code. These tools can be used to generate unit tests, create test cases and increase the effectiveness of the testing phase to improve overall quality.

Translation Tools enable translation of other programming languages for projects where the team must migrate code to other programming languages. The process uses large language models to complete the translation, leaving developers free to focus on architecture.

Documentation Support includes development of documents for code comments, regulatory requirements etc. Prompt Engineering generates summaries and answers questions and provides examples so developers who review the code for later upgrades have appropriate documentation to support the software evolution.

Project Management for all of DevOps is supported by automated routines and integration of information and documentation throughout the process, monitoring system performance, analyzing test results and optimizing implementation. The ongoing analysis of test planning, data migration, compliance documentation and architecture supports the entire DevOps team.

If your business wishes to improve productivity, timelines, budgets and dependability of in-house applications, you will want to find a vendor and service provider who appropriately employs AI and LLMs to support its development model. If you are planning to engage an IT expert to augment your own software product or solution, it is wise to look for this capability when you interview prospective partners. Contact Us to find out how to integrate AI and LLM capabilities into your software project, website, analytics initiative or other project. Explore our free White Papers: ‘What Is AI And How Can It Help My Business,’ and ‘The Practical Use Of GenAI In BI And Analytics Tools.’

Original Post: Look For a Software Development Partner That Uses AI and LLMs!

Understanding GenAI and Agentic AI: What’s the Difference?

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March 19, 2025

Choose or Combine GenAI and/or Agentic AI for Apps

The only way to avoid news of Artificial Intelligence (AI) is to move to the top of a mountain and leave all your devices behind. Talk of AI is everywhere. So, it is no surprise that most businesses are considering how to incorporate artificial intelligence (AI) into their consumer apps, business applications, websites and mobile applications.

Gartner predicts that within the next few months, ‘…40% of enterprise applications will have embedded conversational AI.’

As you discuss AI opportunities with your team and your IT consultant, be sure you understand the terminology. There is a distinct difference among AI technology, products and solutions and the industry often uses the terms interchangeably.

In this article, we will discuss the difference between two types of Artificial Intelligence (AI) development your business may be considering, namely, Generative AI (GenAI) vs. Agentic AI.

Generative AI (GenAI)

This technology is form of AI designed to understand and respond to prompts and to generate text, images (including video) and other media. To function, GenAI models must be trained, using large datasets. By analyzing these datasets, the system can learn to spot repetitive results, trends and patterns. Generative AI utilizes neural networks to recognize and identify these patterns in ‘training’ data, and use that data to generate content.

Here are some of the models in use today:

Multimodal Models

These models can process and integrate information in the form of text, audio, images and video, gestures and facial expressions, etc. Tools like DALL-E, Stable Diffusion, and ChatGPT are based on multimodal models.

Large Language Models (LLM)

LLM is used to understand and generate language. It uses a large volume of data and parameters to train the model.

Variational Autoencoder (VAE)

This model provides probabilistic graphical models and variational methods.

Generative Adversarial Network (GAN)

This machine learning framework consists of two neural networks competing for a ‘win’ or for the best result.

Use Case Examples

Marketing – A business might use Generative AI (GenAI) to create customized, targeted marketing content and social media posts to attract a certain demographic or customer without the need for professional knowledge or human intervention, so the team can focus on critical operations and strategic goals. Using training data, the GenAI model will produce contextual content specifically designed to target customers in a particular market niche.

Reporting and Visualization – When an analytical solution incorporates GenAI within its software or app, it can improve the clarity and precision of the data presented. Using visualization, graphs, images and combining those with summaries and details can provide reports and presentations that are clear and suitable for all audiences, including management and executives, as well as teams and staff members.

Technology – Combine GenAI with search optimization, rules-based systems for natural language generation and chatbots, with simulation, with non-generative ML to classify and segment data, or with graphs. Combining techniques can reduce costs, while delivering appropriate performance, efficiency and accuracy.

For more information about Generative AI (GenAI) benefits and uses, see our free white paper, ‘Generative AI (GenAI): The Benefits And Application Of AI In Analytics.’

Click Here to download the whitepaper.

Agentic AI

This artificial intelligence (AI) approach goes well beyond the ubiquitous platforms such as ChatGPT and other popular AI tools with sophisticated reasoning and iterative planning features to autonomously solve complex, multi-step problems.
  • Flexibility and precision
  • Extended reach and scalability
  • Autonomous capabilities
  • Intuitive capacity
Agentic AI independently and autonomously performs tasks and augments other systems to complete workflow and tasks using tools and processes within a solution or system. It is capable of solving complex problems and taking action and can perform interactive tasks, operating outside the typical machine learning (ML) environment of a classic AI trained model to achieve true process automation.

Use Case Examples

Marketing – Your business might use Agentic AI to automate tasks and schedules, track performance and monitor spending. These AI agents can be categorized to handle specific tasks like creating copy and content, choosing a target audience and monitoring and reporting on marketing campaigns.

Research – Use multi-agent AI models to scan and analyze research, articles and databases and suggest improvements, identify new solutions or products using existing technologies, materials, etc.

Manufacturing – Agentic AI uses sensors attached to machines, components, and other physical assets to predict wear-and-tear and production outages, and sending alerts or initiating processes to mitigate probable issues, avoiding unscheduled downtime and associated costs to manufacturers.

Gartner has predicted that ‘Agentic AI will introduce a goal-driven digital workforce that autonomously makes plans and takes actions — an extension of the workforce that doesn’t need vacations or other benefits.’

Is GenAI OR Agentic AI Right for My Business or Consumer App, or Should I Choose Both?

When GenAI and Agentic AI are combined, the business can build a technology that creates contextual content and is capable of taking autonomous action and making routine decisions, so the enterprise can optimize human and technology resources to scale operations and provide targeted, personalized customer service to enhance customer satisfaction and ensure efficiency and productivity within the organization.

By employing cutting-edge Artificial Intelligence (AI) Technology and expert predictive and data science services, the enterprise can gather, produce and analyze information from disparate data sources, and use that data to create products, enhance services, improve productivity and improve market position, all with the support of a team that is skilled in AI, Data Science, Data Engineering and Predictive Analytics. Contact Us to find out how Generative AI (GenAI), Agentic AI and other AI technologies and services can support your software applications, mobile application, or software product ideas, and advance Digital Transformation (Dx).

Original Post : Understanding GenAI and Agentic AI: What’s the Difference?