The Client developed a specialized niche platform designed to streamline logistics for the cell and gene therapy (CGT) sector. Its innovative, expert solution offers a centralized, seamless interface that allows users to book, manage, and track shipments with multiple specialty couriers, including World Courier, Marken, and QuickStat.
Tag: Digital Transformation Services
The Client is a renowned refinery and industries business in India with a global business. It produces soy bean, refined rice bran, coconut and other related edible oils, as well as personal care oils, bio-diesel and speciality fats. The Client provides cost-effective solutions through augmented productivity, innovation and economies of scale and is committed to cutting-edge technology and processing to achieve its vision and a competitive advantage.
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?
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.
Defeat Resistance to Digital Transformation (Dx) and Succeed in Business!
Studies reveal that Digital Transformation (Dx) in business supports Performance Management, Productivity and Improved Customer Satisfaction. But these same studies also reveal that there is resistance to the implementation of a Dx strategy. The results of business surveys revealed that resistance came from several sectors: 37% CEOs and/or Board of Directors, 32% C-Suite Senior Executives, 26% Department Heads, 18% Middle Managers, 10% Line Employees and 32% said ‘no one.’
‘The Dx strategy is not limited to large organizations. Small and Medium Enterprises (SMEs) and start-ups are also engaging in this strategy to improve results and to create an agile, flexible organization that can respond to changing customer behavior, competitive markets, and the need for team member technology skills and use.’
Given the reported benefits and advantages of Digital Transformation (Dx), it is important that your business consider the concept, and develop a plan to overcome resistance. It is not unusual for businesses to face resistance to culture change, updating or altering popular business processes and upsetting the status quo, or… the way we have always done it.’
When addressing concerns at the management level (which is where most resistance to Dx lies (see survey results above), it is important to use metrics. If you have a chance at changing minds, measurable results and the experiences of other businesses can be an important factor in convincing reluctant managers and executives to spend the time and money to make a change across the organization.
The following results illustrate the benefits of Digital Transformation (Dx) as reported by businesses that implemented the Dx strategy:
- Improved Operational Efficiency 40%
- Any Addressing Changing Customer Expectations 35%
- Improving Product Quality 26%
- Increase Design and Process Re-Use 25%
- Reduce Product Development Costs 24%
- Introduce New Revenue Streams 21%
- Reduce Quality Issues 14%
- Increase First Pass Yield 5%
It is important to note that, as with any other meaningful enterprise change or upgrade, the organization will not change in a day! Technology changes, including artificial intelligence (AI), cloud computing, the integration of data repositories to democratize analytics for business users, the integration of the Internet of Things (IoT0, low-code, no-code development and other technology upgrades take time. The organization must address culture, business processes, approval loops, and access to critical hardware, software, networks and mobile devices in order to capitalize on the prospective benefits of Digital Transformation (Dx). This is an investment in the future!
The Dx strategy is not limited to large organizations. Small and Medium Enterprises (SMEs) and start-ups are also engaging in this strategy to improve results and to create an agile, flexible organization that can respond to changing customer behavior, competitive markets, and the need for team member technology skills and use.
‘Studies reveal that Digital Transformation (Dx) in business supports Performance Management, Productivity and Improved Customer Satisfaction.’
To successfully integrate Digital Transformation (Dx) into your enterprise strategy, your business will need a trusted IT partner to work with your in-house IT team, managers, end-users and others to understand requirements and develop a roadmap to roll-out the strategy, meet expectations and stay within budgetary and time constraints. Engage a skilled, experience IT partner today Digital Transformation (Dx) services, Augmented Analytics For Digital Transformation (Dx), and support for your development and technology needs.
Original Post : How Do I Convince Management to Adopt Digital Transformation?
Can Artificial Intelligence (AI) Improve My Business and Consumer Apps?
It is impossible to listen to the news, read a business publication or browse social media without finding an article or story about Artificial Intelligence (AI).
If your enterprise wishes to consider AI in analytics, and plan for its future potential and growth, it is wise to first understand the state of the technology today, the various ways in which AI can inform and improve analytics for your business, the factors you will need to consider to choose the right analytics solution and the things your business should include in its vendor and solution review.
How Can I Jump Start My Digital Transformation (Dx) Project?
Digital Transformation (Dx) may seem daunting, but with the right planning and execution, a Dx project will reap many benefits for your business.
Digital Transformation Improves Results…As Reported By Businesses!
According to a survey of businesses regarding Digital Transformation (Dx), 40% of respondents reported improved operational efficiency, 35% reported that it was easier to meet changing customer expectations, 26% said Dx improved product quality, and 24% said Dx reduced product development costs.
Some Reasons Your Business Users Should Love Digital Transformation (Dx)!
When it comes to implementing a Digital Transformation (Dx) initiative, your IT team and senior executives probably don’t need convincing! Consider the recent IDC survey results about Dx:
