Curated by: Sergio A. Martínez

And of course, this process of automating tasks and processes is pretty important in every industry imaginable. Let’s look, for example, at software development: A solution already in popular use is Robotic Process Automation (RPA), a way to automate specific tasks within a process, so people don’t have to do them manually. The main advantage of RPA is that it can save time and be more accurate than humans because it’s not necessary to have someone actively monitoring how the task is performed, and ultimately means that businesses can get more done faster and with fewer resources. This allows developers to focus on more complex projects while reducing the time spent performing mundane tasks.

By its very nature, RPA works well with larger applications due to its ability to organize data into streamlined processes, reducing the overall development time and cost, reducing development hours, and making sure everything runs smoothly. Robots make this easy as they don’t need the same amount of troubleshooting, testing, and debugging time as we humans do. In other words, the reason why RPA has become an increasingly popular tool in the software industry is because of its ability to speed up development for faster technology deployment. As stated by IBM:

“[RPA] combines APIs and user interface (UI) interactions to integrate and perform repetitive tasks between enterprise and productivity applications. By deploying scripts which emulate human processes, RPA tools complete autonomous execution of various activities and transactions across unrelated software systems.”

However, with more and more businesses migrating to digital tools and platforms, and software development continues rapidly expanding with no signs of slowing down, the demand for innovative technology solutions also grows. It’s no wonder the development of automatic tools is booming to keep up, helping to optimize tasks during a software project in a way that was unthinkable barely a decade ago. There is no bigger leap forward in automation technology than Artificial Intelligence, which promises to change the field in ways that we maybe cannot grasp yet.

Automatic Intelligence

The use of AI technology is certainly booming at the industrial scale and with good reason. By deploying these kinds of applications, businesses can automate many mundane, time-consuming tasks that would otherwise require a lot of manual labor, while reducing wasted resources and increasing efficiency in the production process. With AI driving efficiency gains, businesses benefit from reduced labor costs and improved production times, making it a no-brainer as far as implementation is concerned. 

It’s no surprise, then, that use of AI technology is booming. This capability has generated enthusiasm from those who understand its vast capabilities, leading to an explosion of use at an industrial scale. And as AI continues to expand, it may become a fundamental component of modern business operations around the world. However, is the implementation of AI tools and an automation process the same thing? Or do these ideas refer to fundamentally different concepts with distinct goals and desired outcomes?

“AI is not the same as automation. Automation is a machine executing a series of instructions exclusively set by humans. If an action isn’t explicitly described in the instructions, the machine can’t do it. With AI, however, the machine can take broad rules outlined by humans, and determine its own pathways to success”, explains the Artificial Intelligence Institute. “Automation can be used in tandem with AI such as machine learning and deep learning to produce even better results in a process we might call AI automation [which] allows us to reap both the business process benefits of automation — increased speed, efficiency, time-savings, and ability to scale — with the insights, flexibility, and processing power of AI technology.”

That way, AI is revolutionizing the robotic automation process and has opened up virtually infinite possibilities for all sorts of industries, enabling robots to react faster and make more accurately timed decisions without direct human input. AI can even give robots the ability to learn from their mistakes, so they don’t repeat them and cause unnecessary delays in production or other processes. All of these advantages offered by AI give RPA tools a new lease of life, making them even better players in today’s automated world. And this can only get better, right?

The “artificial” in Artificial Intelligence

It might seem cut-and-dry to think that AI is an overall net positive on automation processes, but companies should approach AI with caution instead of putting too much trust in it, outright replacing manual decision-making processes without due consideration, because there are often large discrepancies between initial expectations and actual outcomes when working with AI. In other words, while these new tools may promise optimal performance, they don’t always live up to expectations, so any organization interested in these kinds of automation tools needs to bear the limitations of AI in mind at all times.

“When companies place too much confidence in AI, they may miss key opportunities to inject creativity or human judgment into decision-making processes which can lead to misguided actions with unintended consequences”, says Adolfo Cruz, PMO Director, and Partner at SCIO. “For example, AI tools are limited when it comes to making decisions; they can only provide insights based on data and algorithms, and do not possess the same level of judgment as a human. Additionally, these tools lack intuition and creativity and may not be able to think outside the box or come up with creative solutions to unique problems”. 

That is to say, AI has come a long way in developing industrial advancements, yet there are still certain tasks that should be left off limits. AI should not be involved in any decision-making processes due to their lack of understanding of the potential implications of their actions. Allowing the robots to take over tasks such as operating complicated machinery and making decisions over them could do more harm than good when it comes to safety measures for both the workers and the products being created. Even with the best technology and programming, mistakes can still be made due to inevitable flaws in their programming. These risks outweigh any saving benefits that AI machines may provide, therefore we must prevent them from causing any further damage by restricting them in what they can do within an industrial context.

In short, automation and AI represent a powerful combination of resources with exciting potential. With no tedious tasks to weigh them down, people can focus their full power on the challenge or problem at hand and work in tandem with AI automation to create dynamic systems that save time, energy, and money. This combination is already being used across industries to great effect — streamlining production processes that were once complex and solving problems more quickly than was ever thought possible. All of this leads us toward an exciting future where these amazing technologies will continue to do even more positive things for both businesses and consumers. All in all, it’s truly amazing how much these two forces are capable of when we use them together.

The Key Takeaways

• The point of building machines is to reduce the amount of work a person needs to do to produce something, and in software development, this is no different.
• It should be clear that AI and Automation tools do not refer to the same concept, exactly, but should be combined to get the most out of them.
• The main advantage of AI is that it can make its own decision and correct courses, which can be powerful when used with RPA.
• However, this AI application should be careful and considerate, or any organization runs the risk of over-rely on this technology, which can have unintended consequences.

Scio is an established Nearshore software development company based in Mexico that specializes in providing high-quality, cost-effective technologies for pioneering tech companies. We have been building and mentoring teams of engineers since 2003 and our experience gives us access not only to the knowledge but also the expertise needed when tackling any project. Get started today by contacting us about your project needs – We have teams available to help you achieve your business goals. Get in contact today!

Curated by: Sergio A. Martínez

We’ll see a lot more AI-enabled devices in our homes and workplaces, as well as a continued increase in the use of AI for things like facial recognition and target marketing. We may also see some interesting new applications of AI, such as using it to create more realistic virtual worlds or to help automate complex financial transactions. Of course, there will also be plenty of challenges to overcome, such as ensuring that AI systems can operate safely and ethically. But I remain optimistic about the future of AI, and I think it has the potential to truly transform our world for the better.

The AI of today and tomorrow

AI is still in its early developmental stages, which means that a limited number of tools are available for implementing AI. However, some of the most important tools currently available include natural language processing, which is used to analyze and interpret human language, which is essential for developing intelligent assistants and chatbots, predictive analytics to make predictions about future events, trends, and behaviors, and machine learning, used to create algorithms that can learn and improve from experience. These three tools are essential for developing AI applications and will become even more important as AI technology advances. With these rapid developments, AI will become one of the most important tools in various fields, and the trends for 2023 will include…

1) A wider democratization of this tech

AI is no longer the exclusive domain of scientists and engineers. Today, anyone with an internet connection can access powerful AI tools and resources. This has leveled the playing field, allowing people from all walks of life to create and experiment with AI. This increased accessibility has already had a transformative effect on the world, and it is only going to become more pronounced in 2023 and forward. As AI continues to evolve, it will become an increasingly important part of our lives, changing the way we live, work, and interact with the world around us, with a level of quality expectation that will certainly affect the products and services offered by almost every type of business.

2) The rise of prompt engineering

The topic of prompt engineering is one we have touched on before, doing an overview of how this field will become a career in demand in coming years thanks to the increasing popularity of AI tools for general consumption. For those not in the know, prompt engineering is a “Natural Language Processing” area, where you design the final output of an AI system by carefully constructing the instructions for its generative engine. With an application in everything, from art to coding, prompt engineers will become a very in-demand position for organizations heavily investing in AI toolsets, so 2023 will bring a very interesting change in the job landscape.

3) No-code platforms and other generative tools

Speaking of which, generative tools are here to stay. With applications like Dall-E opening to the general public, generative tools are becoming a unique way of approaching problem-solving, allowing their users to explore and experiment with different possible solutions. This approach is well-suited to the rapidly changing field of artificial intelligence, where new challenges and opportunities are constantly emerging. Additionally, generative tools can help to automate the process of creating training data sets, which is essential for machine learning. As AI generative tools become more sophisticated, they are likely to play an increasingly important role in the advancement of artificial intelligence in 2023.

4) Ethical AI

Artificial intelligence is often lauded as a transformative technology that has the potential to revolutionize industries and change the way we live. However, AI also raises significant ethical concerns, which need to be addressed to ensure this technology is as useful and safe as possible. One of the most pressing issues is the lack of diversity in the field of AI, which creates a risk of bias being built into algorithms, as we have seen before, for example, with Application Tracking Systems within the HR field, which tend to be easily gamed, proving inaccurate (or worse) when selecting the appropriate candidate for an open position.

Another major concern is data privacy. After all, AI systems are becoming increasingly adept at gathering and analyzing data. In some cases, they may even be able to eavesdrop on our conversations or track our movements. As a result, there is a real risk that our personal information could be leaked or mishandled.

Finally, there is the issue of transparency. Due to the complex nature of AI algorithms, many experts fear that the opaque nature of AI could be exploited for nefarious purposes, such as mass surveillance or even control of public opinion. Furthermore, the rapid pace of development in AI is outstripping our ability to understand and regulate it, and as a result, there is a real risk that AI could be abused in ways that we cannot even imagine. For these reasons, 2023 will be an essential year to demand greater transparency from those who are developing and deploying AI technology. Only then can we hope to prevent its misuse.

5) Leaps in autonomous systems

In a world that is becoming increasingly reliant on technology, it is no surprise that autonomous AI systems are gaining in popularity. These systems can perform tasks that would normally require human involvement, such as monitoring inventory levels or providing customer service, and even historically riskier fields, like transport and industrial applications are becoming more reliable and cheap enough that 2023 will likely see mass adoption of these tools in everyday tasks. The clear advantage they have by operating around the clock without needing breaks, and their lack of susceptibility to emotions or fatigue is a huge advantage over traditional systems, helping to improve efficiency and productivity in a variety of industries. As more businesses begin to recognize the benefits of these autonomous systems, their popularity will likely continue to grow in the coming year.

Final notes

With all this said, 2023 is shaping up to be the “Year of AI”. The sheer amount of data that will be generated by businesses and individuals will continue to grow exponentially, allowing for better training of AI algorithms, and making them more accurate and efficient. And the cost of computing power and storage will continue to decline, making it more accessible to businesses and organizations of all sizes, with breakthroughs in AI technology enabling humans and machines to work together more seamlessly than ever before. And as long as AI’s ethical concerns will be addressed more seriously, this technology will be increasingly ubiquitous in daily life, both inside and outside of work. All of these factors together make 2023 the year that AI will come into its own and begin to transform the world as we know it. Are you ready to embrace it?

The Key Takeaways

• The rapid evolution of AI technologies has made them a viable tool in plenty of industries, and 2023 can be a landmark year in its adoption.
• Although still in the early stages of development, disciplines like natural language processing, machine learning, and predictive analytics have pushed AI into mainstream usage.
• Specifically, AI will increase the popularity of prompt engineering, generative tools, and autonomous systems.
• This democratization of this tech, while bringing innovation at an unprecedented pace, also has ethical concerns that the industry needs to solve to guarantee a safe implementation of AI in daily life.

Scio is an established Nearshore software development company based in Mexico that specializes in providing high-quality, cost-effective technologies for pioneering tech companies. We have been building and mentoring teams of engineers since 2003 and our experience gives us access not only to the knowledge but also the expertise needed when tackling any project. Get started today by contacting us about your project needs – We have teams available to help you achieve your business goals. Get in contact today!

Curated by: Sergio A. Martínez

And it’s not just big banks and financial institutions that are benefiting from the power of AI — FinTech startups use it to create innovative products and services that change the way we bank, invest and save, bringing more personalized experiences to customers by analyzing their spending patterns and providing tailored recommendations. 

So, while AI continues to evolve, its increasingly significant footprint on the FinTech industry is making financial services more efficient and accessible, playing a crucial role by helping to automate various tasks, from customer service to fraud detection. For example, AI-powered chatbots can provide personalized financial advice, and Machine Learning is being used to develop predictive analytics tools that can help identify investment opportunities, or red flags to watch out for.

As a result, AI will only become more embedded in FinTech, transforming the financial sector by automating processes and providing real-time insights, and helping cut costs. Perhaps most importantly, AI will give organizations the ability to make sense of the vast troves of data they collect daily, using Machine Learning algorithms to identify patterns and trends that would be impossible for humans to spot. As a result, this technology is poised to profoundly impact the financial sector in the years to come.

However, the popularity of AI solutions in FinTech has also raised questions within the industry; after all, with machines driving more financial systems, is their traditional risk management ready to keep pace with an increasingly automatized approach that brings innovations and disruption almost daily? For any business, it’s important to stay ahead of the curve and make sure you are using AI to benefit your customers and your bottom line, and risk assessment needs to be considered to succeed at it. But what will it look like?

Risk assessment in FinTech: A job for robots?

As FinTech companies become increasingly reliant on AI, the need for robust risk management processes is more important than ever. By its very nature, FinTech is a highly innovative sector, which means new risks are constantly emerging. And while AI and Machine Learning can help to identify these risks promptly, as well as monitor any exposure to them by automating data analysis and providing accurate results, gaps still exist.

“One of the main concerns is that AI systems can be biased against certain groups of people, due to the data that they are trained on. If an AI system is only exposed to data skewed in favor of one group of people, it will produce biased results”, says Rod Aburto, Service Delivery Manager and Co-Founder of Scio. “And beyond that, AI systems can be hacked or tampered with, which could lead to disastrous consequences. These tools are still far from perfect, and there is always the possibility that they’ll make mistakes with serious implications, but despite these potential risks, AI remains promising.”

Combining Machine Learning and AI can help financial institutions to make more informed decisions, like assessing the impact of new regulations on a business model or identifying risks associated with their products and services, but the availability of data is an important matter: the final assessment is only as good as the information entered into the system. This means FinTech companies need to be especially vigilant in their risk assessments due to the rapidly changing nature of the information. For example, if a training dataset is predominantly male, a Machine Learning algorithm may learn to associate certain traits with being male, leading to biased results when applied to a broader population. 

In the specific case of FinTech, a way that bias can be introduced is through algorithms that have been designed to achieve a particular outcome, rather than being impartial. An algorithm designed to identify creditworthy individuals is likely to be biased against low-income applicants, leaving people in need of these kinds of services out. 

Another challenge for FinTech companies reliant on AI to provide their services is that they are vulnerable to attacks by hackers who could exploit weaknesses in these systems. Hackers could gain access to sensitive customer data or even manipulate the algorithms used by FinTech companies, leading to disastrous outcomes. So when it comes to FinTech, security should be a top concern, and data breaches and security vulnerabilities can have a devastating impact on both consumers and businesses when machines cannot make critical decisions on their own. That’s why it’s so important for fintech firms to have robust security measures and know the risk involved in pure automatization.

A balanced future in FinTech

“FinTech is an industry constantly evolving, and there are many good practices around risk assessment, but at its core, risk assessment in FinTech should focus on three key areas: regulatory compliance, customer impact, and business resilience”, continues Rod Aburto about the challenges in pure automatization. “And when it comes to implementing AI tech in this area, responsibility, due diligence, and human intervention are key to ensure they work as intended. These machines are more than capable of digesting data and coming up with insights than almost any person but are not infallible. Without human expertise guiding and implementing actual useful results, it’s easy to render any outcome from AI less than ideal.”

AI is revolutionizing the fintech industry at every level, from software development to customer service. According to the International Data Corporation (IDC), “the worldwide market for AI software, hardware, and services is expected to surpass $500 billion by 2024”. As more FinTech companies are using AI to create new and innovative products and services that make financial services more efficient and accessible, it’s important to keep in mind that an ethical, responsible, and effective implementation of AI is one where humans are kept in the loop and can be made accountable for any mistake. AI will only become more embedded in FinTech as the industry evolves, and for businesses, it’s important to stay ahead of the curve and make sure you are using AI to benefit your customers and your bottom line.

So, by conducting responsible and human-curated risk assessments, FinTech companies can stay ahead of the curve and make sure that their products and services are as safe and secure as possible.

The Key Takeaways

• The FinTech sector is one of the most innovative, and technologies like AI and Machine Learning are finding implementations in almost every area.
• AI brings a speed of automation of processes, insights, and results without precedent, and while exciting, challenges arise alongside these tools.
• Traditional risk assessment needs to keep pace with the technological revolution and has to keep a watch out for weaknesses and biases in these systems.
• Human intervention and interaction will still be necessary for the foreseeable future, guiding these systems and achieving their best outcomes.

Scio is an established Nearshore software development company based in Mexico that specializes in providing high-quality, cost-effective technologies for pioneering tech companies. We have been building and mentoring teams of engineers since 2003 and our experience gives us access not only to the knowledge but also the expertise needed when tackling any project. Get started today by contacting us about your project needs – We have teams available to help you achieve your business goals. Get in contact today!