DEV Community: Eastern Peak

Enhancing Your SaaS App Functionality with Third-Party APIs

Eastern Peak — Fri, 23 May 2025 10:03:00 +0000

The Software as a Service (SaaS) market is witnessing unparalleled growth due to the increasing demand for software innovations without investing in expensive in-house IT infrastructure. This allows companies to expand their reach with first-class capabilities. For instance, the global SaaS market is projected to reach $317.55 billion by the end of 2024 and grow to an impressive $1.23 trillion by 2032.

However, competition is becoming more pressing due to the increasing appeal of the industry. SaaS brands recognize the value of third-party application programming interfaces (APIs) as out-of-the-box solutions for their application’s functioning and boosted performance. Integrating third-party APIs allows businesses to stay ahead.

Since using third-party API can boost businesses’ application efficiency and deliver more value to customers, companies should incorporate them into their SaaS products to maintain a competitive edge. Doing so requires knowledge of how APIs work and what objectives business owners should prioritize to make such an adoption possible.

Let’s explore third-party APIs, their key uses, reasons for adoption, and strategies to integrate them.

Understanding third-party APIs

What are third-party APIs

What is a third-party API and how does it work? An API is a program that serves as an intermediary for software systems allowing for data sharing, communication, and collaboration. Essentially, they allow your SaaS to communicate with other software.

Any API has a specific set of protocols that enable integration between the chosen systems, and it’s an indispensable element of modern software. Unlike the native ones, 3rd party APIs are made by an external development team that’s not directly involved with the platform or service it interacts with.

Why use third-party APIs

Business owners contemplating third-party API integration with their application should consider the following benefits:

Faster development

While there are advantages to developing one’s own APIs, software development and adaptation with other systems is much faster with third-party APIs. A company can launch its SaaS much faster without the need for re-inventing the wheel and creating a new API. An out-of-the-box tool enables businesses to utilize the pre-built functions, cutting back on time and giving brands a chance to respond to clients’ needs faster.

Cost efficiency

Developing in-house API solutions can be expensive, and not every company has the budget to work out its perfect alternative. The price for an API can begin at $25,000 and rise from there. A third-party API eliminates development and maintenance expenditures, instead presenting a ready option to launch into action.

Enhanced functionality

A 3rd party API achieves two purposes: it presents the features that improve the app’s quality and offers a finished product at a minimum development cost. It accelerates time-to-market and ensures that your app remains competitive without the need for extensive in-house development.

Scalability

As your app grows, companies can opt for API integration for SaaS to manage increased user demand by offloading certain functions to external providers. This long-term orientation allows enterprises to envision future progress and guarantee better performance of their apps in the future.

Key uses of third-party APIs in SaaS apps

While third-party app integration best practices vary, the list below covers key areas where third-party APIs can add substantial value.

Payment processing

Programs and services in need of processing payments capitalize on integrating 3rd party APIs into their system to handle their financial transactions. Such APIs deliver support for different payment methods and ensure that the process itself goes smoothly, with regard to safety protocols.

Examples of such APIs are Stripe or PayPal; both rely on payment processing operations as a significant part of their business procedures, including billing, fraud prevention, and invoicing services.

Communication

A company can exploit an API for mobile app or service to cover communication features, integrating emails, chats, different messaging types, and even voice functions. Integrating such a feature in many software products is imperative to user engagement.

Third-party API examples for communication purposes are Twilio and SendGrid which provide such capabilities to their clients. These communication APIs allow individuals to get email delivery services, voice calls, and video communication.

Geolocation

Geolocation APIs provide services for determining and utilizing users’ geographic locations. Brands using such third-party integrations retrieve the information from client-side devices, including browser or IP geolocation as the most common ones. For example, Google Maps is the perfect case of when geolocation APIs accomplish their task, giving users location data and directions based on it.

Analytics and tracking

Typically, analytics and tracking APIs collect user information and supply the company with specific characteristics of their behavior or traffic sources within a program. Businesses applying these APIs gain knowledge about their clients and their engagement. Both Google Analytics and Mixpanel present analytics and tracking APIs helping businesses assess user interactions and segment this data.

Access and authorization

Managing clients’ authentication and authorization, these APIs guarantee secure access to applications. They are built around particular security standards and provide mechanisms for user authentication and secure token management. To illustrate, OAuth and Auth0 offer frameworks for authorization and user management that highlight the principles of access and authorization APIs.

Data storage and management

Such API integrations provide flexible solutions for saving and managing application data, such as databases. Some of the typical features these APIs can provide are real-time synchronization and automatic backups. That’s the case with Amazon S3 which proposes scalable object storage for users needing to preserve large amounts of information, reducing the need for maintaining and managing data infrastructure.

Integrating third-party APIs into your SaaS app

Once business owners become aware of the advantages of a 3rd party API, they start asking questions: How to incorporate APIs in your SaaS? What is needed to make the process smooth and benefit from third-party integration? If you or the people responsible for this implementation are non-developers, you’d need to set certain goals and work closely with a developer to avoid any potentially costly errors.

How to choose the right APIs for your SaaS app

Analyze your needs

When selecting an API for app development, the company should set specific demands it has toward features it intends to add or enhance. This process can call for much more effort than you might anticipate: business owners should account for their program profile and the particular functions necessary to make it better.

Identifying these expectations will help them narrow down the API options that best align with their goals. Ask yourself, “What is third party API integration bringing to my clients? Is it improving their experience?” Keep your user in mind whenever you make such decisions.

Evaluate API providers

Searching for the best API providers requires some time. It can be quite a difficult task: in 2021, there were 200 million private and public APIs worldwide. Although it complicates the search, it also means that you’ve got multiple opportunities to choose from even for quite niche industry branches.

Look for companies that have proven to be trustworthy. Analyze reviews, look at your rivals and market leaders to avoid repeating their mistakes or learn from their growth, and check performance benchmarks. Explore 3rd party API examples that highlight prior successes or failures.

The development communities also play a pivotal role in selecting the best API providers: well-documented APIs with active communities will give you better support and resources.

Consider costs and scalability

SaaS API integration has numerous cost implications, so it is critical to account for both short-term and long-term expenses. APIs may charge based on usage, data volume, or user access. Nonetheless, cost shouldn’t be the only factor to analyze: reflect on how the API will scale with your application.

Your perfect API solution must be adjustable enough to handle accumulating client information and operations as you expand and have flexible pricing to manage expenditures.

Best practices for integrating third-party APIs

Explore these strategies for integrating third-party APIs in a mobile app to leverage your strengths and prevent missteps while diversifying your functionality and improving user experience.

Prioritize security

Integration with third-party API always comes with security risks — you don’t control the regulations already in place, so you need to choose APIs carefully. Disturbing 95% of respondents commented on struggling to contain security incidents concerning production APIs.

Business owners should ensure that the chosen API provider complies with industry-standard security protocols, such as OAuth for authorization and HTTPS for secure data transmission.

Regular monitoring and maintenance

As much as it can be tempting to stop after integrating APIs and start working on your core features, it’s a continuous process requiring constant assessment and updates. Regularly monitor API performance metrics, such as response times, error rates, and uptime.

Since using a third-party API requires being constantly informed, it also means that businesses should keep up with updates if the API changes. Businesses often adopt proactive strategies including routine testing and version management. This approach will help your application operate smoothly without crashes or needs for urgent updates.

Implement robust error handling

Even the perfect APIs can become vulnerable to errors or downtime, and while you can’t change that, you can build secure measures when such errors arise. Make sure to add fallback procedures, such as retry logic or alternative workflows. To avoid users’ disappointment and confusion, provide clear messages to explain what’s happening and how soon it can be fixed.

Optimize performance and efficiency

An API integration for SaaS applications depends on how you work with it. As non-developers, business owners should opt for reducing the number of optimizing API calls and minimizing latency.

When it comes to thinking about how to integrate an API, the main question lies in improving its responsiveness and decreasing the load on your service and the API. Every API has its rate limits, so consult a developer team to make sure that the integration stays within them.

Plan for scalability

If you’re planning to grow your service’s reach, your API should be flexible to scale up together with your SaaS. Plan for it from the outset by choosing APIs that can accommodate increased traffic and usage.

Talk to your team and inquire about the API’s ability to expand horizontally in the future. To build a reliable system around the potential future expansion, implement distributed systems to manage high volumes of API requests.

The bottom line

Integrating third-party APIs into one’s application is a strategic move to elevate your company’s capabilities and operational efficiency. Using APIs to deliver better value at a lower cost and without over-investing in development allows your application to adapt and scale up much faster.

As your SaaS progresses, anticipate innovative changes combined with your users’ increasing demands. By staying in touch with your market and ensuring regular updates of your APIs and other tools, you’ll maintain a high quality of your SaaS offers, exceeding your customers’ expectations.

While third-party APIs make your app’s growth easier, integrating it into your SaaS is no easy task if you’re a non-developer and need professional insight. Do you want a fast, flexible, and customized solution? Contact our team and get a free consultation on setting up your system with a third-party API that meets your needs.

See the original article here: Enhancing Your SaaS App Functionality with Third-Party APIs

Top 7 Game-Changing Trends Shaping the Future of SaaS

Eastern Peak — Wed, 21 May 2025 07:10:00 +0000

The global tendency to start utilizing cloud environments has been a game changer in the world of enterprise software. Back in the day, companies had to install and manage their applications locally, but that delivery method has quickly grown obsolete. In 2024, businesses prefer to receive their solutions as a service — over the Internet, with all the hardware needs already covered.

The software as a service (SaaS) market was valued at $192.8 billion in 2023, and it’s growing rapidly. In this article, we’ll explore the technologies that drive this expansion and uncover what innovations are already shaping the future of SaaS.

Read on to learn more about the latest SaaS trends and practices you can leverage to gain a competitive advantage.

Understanding the SaaS

To get a deeper understanding of how the trends we’ll discuss impact SaaS specifically, let’s do a quick SaaS industry overview and take a look at several key market statistics.

SaaS definition

In a nutshell, software as a service outlines solutions that are delivered over the Internet. All the infrastructural elements of such software are hosted on the provider’s servers, so customers don’t need to go through the process of installing and maintaining the needed application locally.

When opting for a SaaS app, users can enjoy a seamless experience, with all the updates being handled by the vendor. They can also access the application from any connected device and scale their software easily as their business grows.

Compared to traditional delivery models, SaaS apps are winning, as they are more cost-efficient. In terms of pricing, customers can avoid the expenses associated with maintaining on-site architectures, and they can typically choose the subscription model best suited to their needs.

Key SaaS market statistics

The SaaS landscape is best defined by numbers. Here are some of the most relevant facts and predictions:

The global SaaS market is predicted to reach over $1,228 billion by 2032. (Fortune Business Insights)
In 2022, companies were using around 130 SaaS applications on average. (Statista)
IT and Telecom command the largest industry market share; however, the healthcare industry is expected to demonstrate the highest CAGR over the period 2024-2032. (Fortune Business Insights)
North America is the largest player in the global market in 2024, generating more than 40% of the worldwide revenue. (Cognitive Market Research)
North America dominates the market largely due to its key players’ early adoption of AI, IoT, and robotics. (Market Research Future)

Top 7 SaaS trends in 2024 and beyond

Developing a SaaS product always involves chasing down the latest technologies and practices to gain a competitive edge. Let’s explore the top 7 SaaS industry trends that are already shaping the future.

1. Integration of AI and machine learning

In 2024, it’s vaguely possible to find a SaaS company that’s not leveraging artificial intelligence one way or another, and for a good reason. AI has grown to penetrate nearly all aspects of business operations.

In terms of analytics, predictive AI can help you gain insight into the SaaS future trends that are likely to be a hit, explore customer behavior patterns, asses the effectiveness of your strategies, and guide general decision-making efforts.
When it comes to optimizing the working process, AI can be a great assistant to your team. One of its main purposes is taking on repetitive tasks and automating numerous processes. By cutting down the manual load that needs to be handled, it can foster more productive collaboration within the team and optimize workloads.
As for enhancing customer experience, AI-powered solutions come in a wide variety of flavors to help with everything from customer service (via chatbots) to the personalization of interfaces and product recommendations.

2. Vertical SaaS solutions

One of the recent trends in SaaS with strong potential for continued adoption is vertical solutions. These apps focus on a narrow niche and cater to a single chosen industry.

Currently, horizontal SaaS is more well-established on the market, with its prominent representatives being solutions like Salesforce and Slack. However, horizontal products in general offer more standardized functions with limited opportunity for customization and typically higher prices.

Vertical SaaS solutions like Riskalyze and Clio, on the other hand, are better equipped to meet particular and complex industry requirements. As a result, they tend to be more cost-effective and ensure better analytics, performance, and customer experience within specific sectors.

3. Customization and personalization

Top SaaS trends have always included personalization, and the importance of this process has not diminished over the years. In fact, according to Gartner’s 2023 research, 70% of customers are willing to share more personal information with a company to receive tailored service if it saves them as little as 6 minutes of time.

Besides saving your customers’ time, personalization efforts should strive to enable them to obtain more value from your product. This can range from regular customization to venturing one step ahead and accurately predicting each user’s needs in record time, helping you gain more new customers.

To achieve such levels of personalization, SaaS companies turn to analytics of available user data, as well as fluctuating market trends and each target demographic’s preferences. AI and ML, in particular, are extremely effective for processing such volumes of data and providing you with actionable guidelines.

4. Focus on security and compliance

Without sufficient cybersecurity mechanisms in place, SaaS products are vulnerable to data breaches and cloud leaks. Such incidents can affect tens of thousands of client companies and even more customers, delivering a hard blow to both your company’s reputation and customers’ safety.

Besides, any SaaS software must be compliant with privacy regulations such as GDPR, HIPAA, and CCPA, and there is no small number of new laws coming into power as new technologies appear on the market.

The emerging policies aim not only to regulate how personal information is treated in evolving technological landscapes but also to respond to increasing users’ privacy concerns. Modern customers value staying in control of their data. They are also more prepared and willing to exercise their Data Subject Access Rights. For instance, according to Cisco, 28% of customers in 2023 exercised DSAR, presenting a 4% increase compared to 2022.

To gain customers’ trust and make sure you are prepared to follow all the applicable regulations, focus on security from the earliest steps of developing a SaaS application. Make sure to select a cloud provider with up-to-date security policies.

Additionally, consider partnering up with a development company that will help you design your app’s security system and audit for any potential regulatory noncompliance.

5. Increased use of APIs

SaaS development is complex as it is, and one reliable way to simplify and optimize the process is utilizing APIs. They allow you to integrate the necessary functionality into your app by using an existing third-party service — no need to develop it natively from scratch. This approach can be handy for adding payment processing features, integrating with social media, adding maps, and a wide array of other features.

Additionally, as far as SaaS trends go, it’s getting increasingly important to use APIs to enable connectivity between your solution and other tools. After all, there is a plethora of SaaS software solutions on the market.

If a customer gets diverted from your application because of one lacking feature, you are more likely to retain them if your product offers a strong API to seamlessly integrate your tool into their existing ecosystem.

6. Mobile-first SaaS

Going mobile-first is a SaaS trend that is growing along with the prevalence of smartphones in our lives. Just last year, it was estimated that around 70% of the global population used smartphones. As users lean on their phones to do everything from shopping and socializing to conducting business, the expectation to have a mobile version of any software is something to consider when building a SaaS application.

Mobile SaaS apps offer flexibility first and foremost. They’re attractive to customers because they bring all the necessary functionality to users’ most accessible devices.

Additionally, when you include mobile platforms in your development plan, you gain the ability to leverage specific features designed for mobile only, thus not only meeting customers’ expectations but exceeding them.

7. White-label SaaS development

Another one of the latest trends in SaaS is white-label development. White labeling refers to purchasing an unbranded ready-to-go product and modifying it according to your needs: you can change the pricing, design, branding, and other aspects before launching your application or reselling it.

This approach offers quite a few significant benefits, particularly to startups. Building a SaaS product from scratch can require a measurable upfront investment. In some cases, the high costs and the task of assembling the infrastructure, functionality, and design can hinder marketing and strategizing efforts.

Opting for a white-label SaaS solution removes the initial development hassle, enabling you to focus on branding and communicating the app’s value to customers.

Staying competitive within the evolving SaaS landscape

The abundance of SaaS opportunities is proportional to the number of companies entering the market. To stay afloat in this fast-paced landscape, you need to go beyond simply implementing new technologies.

Let’s take a look at three approaches to consider to get the best results out of following the SaaS software trends we’ve discussed.

Bridge the gap between trends and customer needs

While keeping up with the latest trends is important, analyzing how each innovation you implement affects customer experience is equally crucial. You can do it by encouraging users to submit feedback and drawing on their insights to assess how effective your app is.

You can also release a pilot version of your SaaS application before the final launch to test how well the core parts of it work.

Additionally, listening to your customers and reconciling your offering with their needs helps dodge potential disadvantages connected to the new trends. For instance, some customers might be wary of AI. If that’s a tool you’re looking to implement, learning about users’ associated concerns will help you design a proper strategy to navigate the situation.

Be flexible and adaptive

The SaaS industry tends to change at a glance. To stay competitive, you need to be prepared to change with it. Stay open to new trends and technologies and foster the same mindset among your employees.

Also, keep scalability in mind when developing and ensure all your solutions, strategies, and architectures are flexible and can be easily modified when there is a shift in the market.

Prioritize privacy and security

The SaaS sector is marked by operating exorbitant volumes of data. With privacy concerns on the rise, it’s essential to take your clients’ safety seriously and establish a responsible brand image.

When creating a SaaS product, implement sufficient security mechanisms, obtain industry-relevant certifications, and make provisions to stay compliant with all applicable data privacy regulations.

How to get started?

Considering the rate at which software as a service is evolving, simply put, the future of SaaS is now. As we’ve seen from the statistical data so far, it’s often a matter of early and smart adoption of emerging technologies that defines whether a startup will beat the competition and claim the top spot.

This makes creating a SaaS business a puzzle with numerous pieces. While there are certain challenges to face, entering this market prepared elevates your chances to stand out and build a profitable, impactful solution.

We’re here to ensure your development journey is smooth and rewarding. Book a call with our team and discover how we can help you build a successful and future-oriented SaaS company.

See the original article here: Top 7 Game-Changing Trends Shaping the Future of SaaS

Agentic AI Explained: Transforming Industries with Autonomous Intelligence

Eastern Peak — Thu, 15 May 2025 07:35:19 +0000

Today, artificial intelligence (AI) is everywhere—it’s successfully integrated into healthcare, HR, content creation, and everything beyond. This technology is here to stay, and more companies are embracing this shift.

The numbers for AI exceed almost every other technology out there: the market size for AI in 2025 is projected to grow to $243.72 billion, with a CAGR of nearly 28% from 2025 to 2030. It’s probably unsurprising, then, that AI doesn’t stay in place and continues developing. While earlier models were relatively limited and required significant human input, today’s AI is adaptable and leverages deep learning and neural networks to grow more creative and solve diverse challenges.

Now, a new step in AI evolution is here—agentic AI. Not limited by the constraints of traditional AI, agentic AI operates with autonomy, continuously learning, making decisions, and taking actions with minimal human intervention.

The global market demand for agentic AI tools will jump: In 2024, its value was around $5.1 billion, but in 2030, it’s expected to reach $47 billion. By combining the new technological freedom and ability to learn with the experiences of the previous models, agentic AI will revolutionize all industries.

This article will discuss agentic AI definition and agentic AI vs. traditional AI, provide agentic AI use cases, and answer the question “What are the potential risks associated with agentic AI?”

What is agentic AI?

Let’s start with the easy stuff: what does agentic AI mean? You are already familiar with what AI does—it usually analyzes data and generates content based on the input. However, agentic AI is different. Agentic AI is a system that operates with a high level of autonomy and primarily targets problem-solving, decision-making, and developing new solutions to complex challenges.

The key features of agentic AI are:

adaptability;
autonomy in decision-making;
reinforcement learning;
usage of large language models (LLMs), machine learning (ML), and natural language processing (NLP);
better contextual understanding;
limited human involvement and
high level of integration with external systems.

Now that this is clear, how does agentic AI differ from traditional AI systems?

Traditional AI, already effective enough, significantly relies on input to continue making decisions and growing. However, agentic AI is proactive and uses goal-oriented reasoning to set specific tasks and adjust based on the context of the situation. This leads to another difference: traditional AI is limited by specific scenarios, while agentic AI understands context and changes its behavior in real time.

How these types of AI handle tasks also differs: the traditional model is more single-task-focused. In contrast, the agentic one can handle multi-level issues and involve complex problem-solving. Both AIs can learn, but traditional AI uses mostly past situations to refine its further actions—it’s different for agentic AI that continuously refines strategies and can predict situations that haven’t yet occurred.

Such a shift illustrates the rapid advancement of how machines interact with the world and their role in improving people’s lives.

Agentic AI use cases in different industries

What industries are most likely to benefit from agentic AI? From self-driving vehicles to intelligent customer service assistants, these agentic AI solutions assist humans in the most demanding environments.

Agentic AI in transportation

Most people can easily envision agentic AI in transportation because it’s been around for some time. You’ve heard about autonomous vehicles: agentic AI enables them to actively perceive their surroundings (traffic, road situation, weather conditions, etc.) and make split-second decisions.

These AI-driven systems process real-time sensor data from cameras, LiDAR, and radar to detect and understand the physical environment, immediately updating if something changes.

The autonomous vehicle market share in 2022 was almost $105 billion and is expected to reach nearly $615 billion in 2030. With agentic AI, traditional self-driving vehicles don’t just rely on rules but continuously adapt to new driving conditions, which improves safety on the streets.

Agentic AI in healthcare

Have you heard of the robots or programs that help doctors perform operations or diagnose illnesses? That’s how helpful agentic AI in healthcare can be, and the opportunities are growing every day. Agentic AI enhances diagnostics by analyzing vast medical datasets, detecting patterns that human doctors might miss, and continuously refining its accuracy.

Just last year’s research publication has found that AI has outstanding accuracy rates, even achieving up to 92.5% performance success in some risk assessments for different health conditions.

In surgeries, AI assistants can perform the precise movements that can be too difficult for human agents due to simple limitations of their bodies. For example, mistakes from overworking, stress, or even shaking hands can be finally minimized.

Agentic AI in finance

The finance market, from trading to banking, is lush for AI integrations—this technology allows companies and individuals to make smarter decisions and increase their wealth. Even more so, they grow increasingly helpful for fraud prevention and security measures.

Unlike rule-based fraud detection systems, agentic AI learns from evolving fraud patterns, adapting its detection methods in real time to counter emerging threats. Trading, on the other hand, gets easier as this technology makes decisions based on data-driven strategies.

Statistics reveal that AI in finance is actively used today: The AI market size in fintech is $42.83 billion worldwide, and as it gets easier to integrate, it will take up more space and offer new solutions.

Agentic AI in manufacturing and supply chain management

There are plenty of opportunities for agentic AI in manufacturing: certain areas require better performance by adjusting workflow, predicting equipment failures, and optimizing resource allocation.

While the data on agentic AI remains limited due to how novel this AI branch is, there is valuable information on how this technology is generally used. In 2020, quality control had the most use cases for it (59%) in the manufacturing industry, with inventory management (44%) and monitoring/diagnostics (32%) following it.

In the supply chain, agentic AI can assist professionals with inventory tracking and demand forecasting, reducing expenditures on potential prediction errors.

Agentic AI in logistics

Logistics is one of the industries where the opportunities of agentic AI can be useful on all levels. In 2024, AI in logistics reached almost $18 billion and is expected to grow to $26.35 billion.

With agentic AI, this technology can help with smart routing and 24/7 shipment tracking. As a result, companies can minimize losses due to delays or wrong delivery. In warehouses, autonomous robots can manage inventory and sort packages.

Smart cities and infrastructure

Urban environments are experiencing a rapid transformation, with traditional views on how cities should look becoming redundant. Today, urban planning is more than just creating skyscrapers—it’s about making green areas and inclusive spaces for all.

Agentic AI can contribute to this by improving energy consumption, planning building allocation, and enhancing public safety, cleanliness of air/water, and more. As cities become more connected as systems, they can provide information about traffic, accidents, or even infrastructure maintenance needs.

Customer service

Customer service already readily utilizes AI to handle routine tasks and respond to repetitive inquiries. In 2024, the most popular use cases of AI in contact centers were voice authentication and process automation (both 37%).

However, as agentic AI can handle more complex tasks, customer service will likely provide more services and opportunities. It will handle complex interactions or predict customer behavior during interactions. This change will shift repetitive and (sometimes) frustrating interactions toward more natural and practical solutions.

These agentic AI applications reveal how diverse they can be. However, what industries are currently benefiting the most from agentic AI? Healthcare, logistics, and manufacturing are the most likely answers.

Examples of agentic AI in action

For those still asking, “How does agentic AI differ from traditional AI?” the case studies below can provide impressive examples of the newest technology adaptation.

Ema—agentic AI in customer support

Ema brings the latest experiences of agentic AI into its tools. It offers an AI chatbot, agent assistant, agent QA, and knowledge base assistant. This agentic AI example claims to resolve up to 70% of customer issues with its AI bot and save over 80% of agent time with its agent assistant. It’s an adaptable service that moves from responding to inputs and can be used as a tool for collaboration with consultants.

Juna.ai—an agentic process control platform

Juna.ai is a platform that uses agentic AI to control its clients’ industrial processes. Among all agentic AI examples in this list, it takes the top place for innovation. It tracks plant processes, optimizes production, and reduces energy consumption. It follows all the plant procedures and generates reports on demand. Its real-time updates with continuous improvement suggestions rely on agentic AI’s novel tech opportunities.

Atomwise—agentic AI in drug discovery

Atomwise uses agentic AI to discover drugs with the help of its technology, AtomNet. With contextual adaptation and fast learning, it studies chemical datasets to predict molecular behavior and potential drug performance. The company compares its technology to image recognition. The pharma industry currently taps into AI-powered molecular simulations and data analysis to develop new drugs or discover their inefficiencies.

Waymo—self-driving cars

Waymo has developed Waymo Driver, which leverages the latest agentic AI to offer a completely hands-off experience for passengers. You have probably heard of similar examples of agentic AI, but many of them aren’t really the same and rely on humans for control.

According to its website, Waymo emphasizes safety and has “millions of miles driven on public roads and billions of miles in simulation,” which has enabled the company to make an independent driver. It maps out the environment and keeps track of external and internal factors affecting the drive.

These agentic AI startups demonstrate how to respond to the already existing need and turn it into something unique.

Challenges and risks of agentic AI

Despite the undeniable potential of agentic AI, it’s not immune to threats and challenges, especially since it’s so new. Businesses planning to adopt it and asking themselves, “How to create agentic AI?” should be aware of the risks to ensure they know how to address them beforehand. So, the question you should ask instead is, “What are the main challenges in implementing agentic AI?”

Ethical concerns and bias

With AI, there’s always a danger of bias due to the datasets it’s trained on. If not properly addressed, these biases can lead to unfair outcomes in hiring or law enforcement, for instance, where they can hurt vulnerable populations.

What are the ethical considerations associated with agentic AI? It grows more autonomous and no longer requires human input—this will create questions of whether technology should be so freely making decisions that affect humans without much control.

Predictability and transparency

Unlike traditional AI, agentic AI dynamically learns and adapts, leading to a less predictable decision-making process. Such a fast agentic AI development and improvement makes it more difficult to control. This technology has not been studied entirely.

Many businesses still ask, “How does agentic AI work?” only after implementing it, which can cause problematic outcomes. It’s still not entirely clear how these AI technologies will perform in high-stakes situations, especially in healthcare, politics, finance, or criminal justice.

Plus, the lack of transparency makes AI auditing more complex, leading to a particular limitation of innovation management.

Security risks

Agentic AI automation can be a target for security threats as it starts to handle sensitive and financially valuable data. If it’s accessed, it can wreak havoc on the business it attacks. There’s also a risk of error—even the best technologies can fail, which can lead to catastrophic results if they control critical infrastructure or financial markets.

Cybercriminals can also use the same technologies to attack private or public resources or integrate into the areas we have highlighted above.

Shaping tomorrow

The groundbreaking shift with agentic AI we are witnessing will revolutionize how we perceive the integration between humans and technology. Businesses that want to stay competitive should leverage it to optimize their performance and enhance problem-solving before they get left behind.

Need help determining how to build agentic AI or integrate it into your operations? Contact us. We’ve got experience with the latest industry trends and know how to make a unique product for your budget and vision.

See the original article here: Agentic AI Explained: Transforming Industries with Autonomous Intelligence