The Client has a start-up business in the United States. This Client is focused on the recruitment technology market. Its business focuses on improving efficiency and quality of the complex process of sourcing in the recruitment industry. The Client business mission is to leverage artificial intelligence (AI) to improve the efficiency and speed of sourcing the best candidates.
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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
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.’
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?
DeepSeek Reveals the Potential for India’s AI Market
The shock waves from the DeepSeek announcement in the artificial intelligence (AI) space are still being felt. As AI technology businesses, software developers and consumers digest the new reality, there is no doubt the market will shift, adapt and change in a drastic way.
At the heart of this change is the Chinese company, DeepSeek, a new venture that has achieved a significant breakthrough in inference speed, leapfrogging over previous, world-renowned AI models like OpenAI, and causing a massive derailment of chip-maker Nvidia’s stock by proving that lower-end chips can be used to achieve high-performance results in the AI space. This open-source market entry has radically changed the U.S. and global market and, in so doing, it has also changed the mindset of AI developers and investors in other countries, including India.
Prior to the DeepSeek announcement, the prevailing AI strategy was a scenario in which a business required a huge capital investment to build Large Language Models (LLMs) for training and to fund massive processing capabilities and a huge talent pool for development. That meant government support, and an industry and environment to achieve these multi-billion dollar investments and goals.
DeepSeek built an AI product for less than ten million USD, with only 200 engineers.
That reality has shifted the India AI landscape by proving that the India software industry can move beyond an AI app focus to create base models and fully functional concepts. In fact, India has done it before! In defiance of all common expectations, India’s ISRO space program reached the moon at a fractional cost of the U.S. NASA program.
So, why not now? India (and other countries) have often watched from a distance as their own technology talent developed the best and brightest applications in the U.S. Today, the India government has the opportunity expand the capabilities of AI within the country, going beyond chatbots and AI contextual applications to leverage the technology talent within its borders and Create Solutions For Government, Agriculture And Other Industries.
The media and industry publications like to use the word ‘gamechanger,’ but in this case, the revelation of DeepSeek is a gamechanger in the true sense of the word, especially for India. The government is now supporting the new concept of AI evolution and development with the acquisition of 10k GPUs to support development and building the infrastructure to roll out AI models in India within 4-6 months. Yes, it’s possible!
Union IT Minister Ashwini Vaishnaw recently announced that, ‘the planned compute facility (cloud-based servers that are geared to run and handle AI inference), Vaishnaw stated that it has exceeded initial expectations with the country securing more than 18,600 GPUs. Among these are 12,896 Nvidia H100 GPUs, 1,480 Nvidia H200 GPUs, and 742 AMD MI325 and MI325X GPUs. Originally, the target was to procure 10,000 high-end AI chipsets. “DeepSeek AI was trained on 2,000 GPUs, ChatGPT was trained on 25,000 GPUs, and we now have 18,000 high-end GPUs available,” the IT Minister said.
As the technology market evolves, we can expect to see more changes, and those changes will come faster and more frequently. DeepSeek is just one example of the need for India to establish a nimble, adaptable approach that will respond quickly to new developments and identify the opportunities for growth and application of these developments in the global and local market.
The game is changing, and India no longer needs to defer to the U.S. or other countries in the AI market or in the use of its own development talent and investment infrastructure. It can build an ecosystem that will stand on its own without deference to other market leaders.
As IT Minister Vaishnaw said, ‘India will offer the cheapest compute in the world at less than $1 per hour for high-end chips that power generative artificial intelligence (GenAI) as the government’s ₹10,000 crore IndiaAI Mission comes into play….’
There is much to research, investigate and understand about the most recent DeepSeek development. But it does prove one thing. We do not need complacency or acceptance in technology. We need innovation, and India is up to the challenge!
Select an AI, partner for Artificial Intelligence Application Development, or a partner for predictive analytics and technology partner and a solution Augmented Analytics Solution With Artificial Intelligence (AI) components to ensure affordable, flexible solutions that every user can leverage, no matter their skillset or technical capabilities. Read our White Papers, ‘Generative AI (GenAI): The Benefits And Applications Of AI In Analytics,’ and ‘The Practical Use Of GenAI In Business Intelligence And Analytics Tools’ and explore the benefits of AI in analytics and the full spectrum of benefits and advantages of current artificial intelligence (AI) technologies.
Original Post : DeepSeek Unseats U.S. AI, and Reveals India Potential!
Use Agentic AI for Autonomous Workflow and Task Completion
Artificial Intelligence (AI) is advancing, evolving and changing at lightning speed. It is nearly impossible to keep up with the changes, and to understand what, if anything, each of the new products and developments can offer to a business.
Artificial Intelligence (AI) Can Take Apps to the Next Level!
The renowned technology research firm, Gartner, predicts that by 2027, ‘more than 50% of GenAI models in use by enterprises will be specific to either an industry or a business function.’
Is GenAI Right For Your Business?
You don’t have to be in the technology business to know about Generative AI (GenAI). The buzz about this technology advancement is everywhere! The media is talking about its impact, governments are discussing regulation, and technology companies are looking for ways to integrate GenAI into existing products and to create new products that will excite consumers, and improve productivity, results and revenue.
The Client is a start-up healthcare technology company, based in the United States. It takes a holistic approach to overall health by focusing on nutrition and lifestyle, with the goal of decelerating the aging process and providing better quality of life.
Can Generative AI (GenAI) Help My Business?
Whether you are in the business of technology, or an average citizen, there is no doubt you know about Artificial Intelligence (AI) and you have probably heard or read about the advances made in Generative AI (GenAI).
According to Gartner business surveys, GenAI has become one of the most adopted and deployed technologies, and it is either in use in many industries and businesses, or it is in the works.
As a senior manager in a software business, or a corporate CIO, a software engineer or a consumer, you are probably thinking about how you can use GenAI to make your product better, or your life simpler. If you ARE in the business of technology, you may already have started a GenAI project.
But, it may be wise to exercise some caution. You know the old adage, ‘just because you can, doesn’t mean you should?’ That certainly applies to GenAI.
Yes, this technology has advanced enough to offer some value in some instances, but it should not be widely adopted without understanding its current limitations. Don’t let the promise of GenAI blind you to the fact that it is not yet a mature technology and that it is not suitable for all applications.
Before you start your project, you should consider the following factors:
- GenAI alone is not the magic potion many think it is. In fact, the best use of GenAI is as a component of a holistic landscape of technologies, which may or may not include other types of artificial intelligence (AI) techniques.
- Business use cases are a wise addition to your strategic discussion. How and where will your business use GenAI and does the addition of this technology add value or provide competitive, productivity or collaborative improvements? Implementing GenAI just because it is cutting edge, does not add value to your organization.
- The cost of implementing these new technologies must be considered. That consideration should include the estimated useful life of the investment and its return to the organization.
- For some tasks like content summarization for presentations or reports, or routine content creation, standard product descriptions, etc., GenAI may be a welcome addition, and will provide productivity improvement for your team.
- When considering the use of GenAI, it is important to understand how and when your team will use the capabilities and set reasonable expectations for its use. If and when you decide to implement GenAI, it is equally important to train and inform your team and help them understand what they can achieve with this technology. You must also ensure that the team understands what GenAI will NOT do for them. There is a lot of hype out there, and team members may think that GenAI is going to either a) replace their position, or b) give them back 50% of their time for other tasks. It is likely that neither of those scenarios will be true, so be sure your team understands the transition, what they can expect, and what you will expect of them.
- Involving experienced team members in the AI process is imperative. You can’t ‘set and forget’ your tasks without risking incorrect output or issues that will affect customer satisfaction or put your business at risk. Consider how and when you will monitor and manage output and what human intervention is required for the use you have imagined in your use cases.
- While we are on the subject of expectations, let’s remember that, while the future of GenAI is promising, the current state technology is not a boiler plate. It is not a one-size-fits-all solution that can be hurriedly put into place, nor will it solve all your problems.
There has been much marketing hype about GenAI, but at the end of the day, if your business is going to invest time and money in this technology, it must establish a reasonable strategic initiative with measurable metrics and risk assessment and management reviews.
Before your business tackles a GenAI investment project, and all the technology, cultural and management changes that it requires, ask yourself a) what problems does my business have and what are our most important priorities, b) Can GenAI realistically help our business solve or reduce these problems and c) how can I measure and manage this new approach to prove my theories?
As we have outlined in this article, it is important to recognize the limitations of the current Generative AI (GenAI) solutions, and develop a thorough and complete understanding of your prospective business use before making a decision to invest in and implement this type of solution in your organization. Contact Us to find out how we can help you plan and achieve your goals. Artificial Intelligence (AI) in Analytics, Artificial Intelligence Development, White Paper: What is AI and How Can It Help My Business? Explore our articles on AI: Generative AI, the Benefits and Applications, Ideas to Get You Started with Generative AI, Understand AI, OpenAI and Chat GPT.
Original Post : Generative AI (GenAI) Is NOT a One-Size-Fits-All Solution!
