As long as the market or societal needs change and technological innovations continue, we’ll always have emerging technologies

For example, more people are using blockchain to execute contracts because it’s safer. And that is causing its popularity to rise. 

Also, many corporations, like General Electric and Siemens, are embracing artificial intelligence (AI), the Internet of Things (IoT), and automation to streamline manufacturing processes. 

Microsoft researchers even released a paper claiming that GPT-4 showed “sparks of artificial general intelligence (AGI).” 

This feat wasn’t supposed to happen for the next 20 years! In short, a lot is happening. 

So, why don’t I break down the software development trends bound to change the industry, regardless of which sector you are in? 

Let’s begin.

I recently wrote an article on Windows Copilot, detailing everything you need to know. I laid out the pros, cons, and in-betweens. Check out the article here: What Is Windows 11 Copilot: Do You Need It and How to Disable It.

Let’s quickly look at the stats before we go into the actual trends.

  • About 48% of software development companies globally will integrate AI projects into their projects in the next two years
  • It’s estimated that the rate of employing IT developers in the US will see a 22% increase by 2029
  • 61.5% of IT teams still use the Agile method for development. Scrum and Waterfall methods came in second (23.1%) and third (9.6%). 
  • According to Statista, the total global corporate investment of $92 billion into AI in 2022 was a slight reduction from the previous year. However, AI investment has increased significantly since 2016, indicating how important AI is for business, even though there was a temporary decrease in 2018
  • A 2022 survey from Gartner showed that 80% of executives believe they can apply automation in every business decision. In other words, companies are moving away from a tactic approach to AI and using artificial intelligence more strategically. 

Software Development Trends: Market Overview in 2024

Software Development Trends: Market Overview in 2024

Now, let’s talk about the latest technologies in the software industry that will totally blow your mind!

Also read: Windows 12 Release Date and Upcoming Features: What You Need to Know

The Latest Technologies in the Software Industry

If you’re ready to be mesmerized, check out the top software development trends below. Go through these AI advancements and see how you can adapt, expand, and prepare:

Artificial intelligence (AI) and machine learning (ML)

AI continues to evolve, giving businesses new forms of innovation, and that is opening new possibilities.

One promising area is natural language processing (NLP), which helps computers analyze and interpret human language.

Also, developers are using AI-powered coding tools more frequently now. This significantly reduces human errors and improves speed.

For example, Github Copilot can generate code snippets and entire functions for developers in real time. 

Furthermore, AI analytic tools like Tableau are helping businesses get a deeper understanding of their data more efficiently than ever!

Real-life examples of AI and ML in various sectors: 

  • Image and video processing. Artificial intelligence and machine learning can analyze images and videos and use algorithms to understand and extract necessary information, like object recognition. 
  • Predictive analytics. Machine learning models can analyze extensive datasets to determine where software will fail and identify performance bottlenecks. This helps developers resolve issues before they cause major damage.
  • Github Copilot is a tool that can help you complete snippets and code instantly. It provides suggestions as you type, which speeds up coding time and decreases the overall development process.
  • Automate tasks saving you time and improving efficiency
  • Supports decision-making based on data
  • Creates opportunities for innovation and explores new ideas
  • Can be biased because it relies on datasets
  • Some users may find it difficult to understand and interpret AI and ML models
  • There are some ethical considerations when it comes to privacy, fairness, and accountability

Generative AI

Generative AI is one of the newest software technologies that is revolutionizing various industries by generating content that looks like a human created it.

Gen AI is used in generating text like ChatGPT, synthesizing images like Midjourney, and even composing music.

Now, this latest computer technology is having a tremendous impact that is reshaping industries, from finance and agriculture to sciences and entertainment.

Real-life examples of generative AI in various sectors: 

  • Life sciences. Through generative AI, researchers and clinicians can give accurate diagnoses by helping them generate high-resolution medical images, like MRIs and CT scans. In fact, some medical institutions are now using virtual nurses and chatbots to provide personalized care for patients remotely. 
  • Finances. Generative AI helps financial institutions analyze risk assessment, algorithmic trading, and fraud detection. There are also AI-driven robo-advisors that offer personalized advice to investors.
  • Marketing and advertising. Marketers use generative AI to create personalized ads and product recommendations based on the customer’s preferences and behavior. They also use AI-driven chatbots to converse with customers to boost conversion rates and customer satisfaction.
  • Saves time and money by streamlining content creation
  • Analyzes data to provide valuable insights and accurate predictions
  • Gen AI offers enhanced creativity
  • Gen AI raises ethical questions concerning privacy, misinformation, and intellectual property
  • Prone to biases
  • Requires specialized knowledge and expertise

Internet of Things

Even though the Internet of Things (IoT) originated 15 years ago, it’s considered an emerging technology because it keeps improving.

IoT makes systems more intelligent and improves decision-making, and it’s becoming a crucial part of businesses today.

Statista estimates that there will be more than 29 billion IoT devices globally in 2030. 

We’ve already seen businesses using IoT to track goods and automate irrigation to control production lines. 

Smartwatches, dishwashers, cars, smart TVs, etc. are all examples of IoT-enabled products you may have right now! 

We can now lock our doors remotely, monitor our fitness with devices like Garmin, and speed up medical care. The possibilities for the future of software development are endless!

Real-life examples of IoT in various sectors: 

  • IoT in wearables. Wearable devices like watches have biometric sensors that can detect temperature, heart rate, respiration rates, etc., to track your health. Interestingly, global consumer IoT technology is expected to reach $616.75 billion by 2032
  • Agriculture. Farmers are using the Internet of Things to improve production yields using smart greenhouses, smart irrigation, and prediction farming.
  • Manufacturing. Manufacturers are using real-time device monitoring to predict maintenance and improve machine health. They are also combining IoT-enabled sensors with EAM and CMMS to improve a machine’s physical life and ensure that it’s reliable and always available for use.
  • IoT is easy to access
  • Makes communication easier
  • Increases productivity
  • Helps businesses save money on production costs
  • IoT can be complex
  • Devices created by different manufacturers may create compatibility issues
  • Users’ privacy and security may be at risk
  • Users can become addicted to the technology

Related: Internet of Things (IoT) Security: Issues and Solutions


When people think of blockchain, what comes to mind is Bitcoin and other cryptocurrencies like Ethereum or Dogecoin. But it provides security benefits beyond just digital currencies.

Think of blockchain as data where you can only add and not change or remove it. This creates a chain of data that is securely linked to the previous one.

Blockchain is highly secure because no one can change the previous blocks. On top of that, it works on a consensus mechanism, so no one can change or control the data.

Because of that, you don’t need a third party to verify transactions.

Real-life examples of blockchain in various sectors: 

  • Transferring money via blockchain. Apps for sending cryptocurrencies exploded in the 2020s because of how it saves financial companies money and time. Blockchain streamlines financial processes by removing bureaucratic red tape and creating a real-time ledger system. It also saves money by decreasing third-party fees. 
  • Smart contracts are like regular contracts. But the difference is that the contract rules are enforced on the blockchain in real time. This cuts out the middleman and enhances accountability for all the parties involved.
  • Advanced security. Did you know that Americans suffered losses of up to $8.8 billion in investment fraud and scams in 2022? These scams happen in various ways, from forged documents to hacking personal files. Storing sensitive information on a decentralized blockchain ledger can dramatically reduce these scams.
  • Blockchain offers better transparency than other alternatives
  • Low operational costs
  • Blockchain supports immutability. That means no one can replace or erase recorded data
  • Improved confidentiality and security
  • Blockchain is more costly to implement than traditional databases
  • You can’t easily modify data once it’s recorded
  • Blockchains are costly to run
  • Blockchain transactions take longer than traditional payment methods

Edge computing

Cloud computing has become a major player, with services like Google Cloud Platform and Microsoft Azure dominating the market. 

However, edge computing is one of the newest software technology trends that organizations are moving to because of the massive data they have to deal with. 

The reason is simple. Cloud computing causes latency because of the time it takes for data to travel from a device to the cloud servers and back.

This is due to the server processing time, bandwidth limitations, distance, and internet traffic. But edge computing solves that by processing data at the end of a network, near the data source. 

Edge computing reduces latency because it doesn’t need to send data to a centralized data center. 

Real-life examples of edge computing in various sectors: 

  • Autonomous vehicles. In truck platooning, edge computing can make it possible to remove drivers from all trucks except the lead driver because the trucks can communicate with each other with super-low latency. 
  • Manufacturing industry. Manufacturers can use edge computing to optimize their production process by using sensors to process data on factory floors. By doing this, they can detect problems, boost efficiency, and decrease downtime.
  • Retailers are also using edge computing to offer better customer experience. They use the in-store sensors to process data, which helps them adjust their store layouts and product placements to boost sales and satisfy customers.
  • Improves response time and latency
  • Reduction in transmission costs
  • Ensures data security and privacy
  • Offers a less expensive route to versatility and scalability
  • Some geographic regions may be at a disadvantage
  • Requires more storage capacity
  • The cost of implementing is high
  • Edge computing needs advanced infrastructure
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Virtual reality (VR) and augmented reality (AR)

Virtual reality transports you to a carefully designed, digital world that feels incredibly real. That said, AR immerses you in an environment, while VR enhances that environment.

More businesses are hosting their applications in the metaverse and virtual environments. 

Even though this emerging technology is primarily used for gaming, it’s also been used for training in simulation software like Euro Truck Simulator. 

Also read: Augmented Reality vs. Mixed Reality in AI Era

We can expect AR and VR to grow in popularity and combine with the other software development trends discussed in this guide. 

Real-life examples of AR and VR in various sectors: 

  • Shopping, marketing, and advertising. Some companies have incorporated AR and VR technologies into their businesses. This has allowed their customers to, for example, try products before buying. A good example is how IKEA uses AR to allow their customers to see how their furnishings will look in their homes before going to the shop. 
  • Healthcare. Doctors can project health indicators on their AR gadgets to help them access instant data on their patients. They can also use VR to test pre-surgery models or help in surgery.
  • Education. Students are using AR and VR applications to improve their learning experience in the comfort of their homes. Another example is Google Arts & Culture, where students can take virtual field trips.
  • AR and VR offer global and remote learning experiences
  • Offers immersive learning experience
  • Offers a better experience than videos and still images
  • AR and VR can become a distraction for some students
  • Extended exposure can cause motion sickness or discomfort for some people
  • Limited content and integration

Advanced robotics

Advanced robotics integrates artificial intelligence into robots to enable them to perform complex tasks and autonomously engage with real-world challenges.

These robots can analyze vast amounts of data, adapt to dynamic environments, and make quick decisions using deep learning and neural networks.

Furthermore, the robots use enhanced sensor technology to better understand their environment.

Modern robots, like Boston Dynamics’s Atlas, are specifically designed for real-world applications by incorporating the principles of human-robot collaboration. 

Real-life examples of advanced robotics in various sectors: 

  • Construction industry. Construction engineers use robots for bricklaying, demolition, automated drilling, access to extreme environments, etc. This reduces the risk associated with such activities. 
  • The mining industry uses advanced robotics to mine hazardous terrains and keep personnel safe. They also increase speed and efficiency without causing harm to the workers. 
  • Healthcare. Advanced robots are used in neurosurgery, therapeutic massage cobots (collaborative robots), surgical assistants, etc. 
  • Advanced robotics increases productivity
  • Ensures products consistently meet standards
  • Works effectively in hazardous environments
  • Advanced robotics may cause potential job losses
  • Higher initial investment costs
  • Lack of skilled personnel to operate the robot


One of the latest technologies in the software industry that caught my attention is genomics! 

Genomics is a technology that delves into the gene’s composition, DNA, structure, and mapping to identify health complications. 

This helps to provide solutions before the problem gets out of hand. 

Real-life examples of genomics in various sectors: 

  • Healthcare. Genomics is an emerging technology that is revolutionizing healthcare through personalized medicine. For example, geneticists can identify hereditary diseases like cancer in an individual and start treatment before it becomes worse. 
  • Biotechnology. Biotechnological advancements, including gene editing methods like CRISPR-Cas9, have their roots in genomics. Researchers can use these tools to precisely alter DNA to study gene function, create disease models, and potentially treat genetic disorders.
  • Environmental science. Environmental scientists use genomics to monitor biodiversity, evaluate ecosystems, and support conservation initiatives. Researchers use DNA barcoding techniques to identify species from soil or water to help in their biodiversity studies and environmental monitoring.
  • Genomics offers personalized care for patients
  • Minimize side effects patients experience
  • Prevent diseases before they grow and cause potential death
  • Genomics raises ethical concerns in terms of privacy, consent, and misuse of genetic information
  • Sometimes, it doesn’t always provide accurate predictions of the disease
  • Genomic technologies and services are expensive
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You may be wondering how cybersecurity is one of the newest software technologies . It’s not. However, it’s evolving rapidly, just like other technologies.

One reason for cybersecurity’s growth is that cybercriminals are constantly bringing new threats. And that’s not ending anytime soon.

So, cybersecurity will always be part of the latest computer technologies as long as hackers exist.

It’s no wonder that 60% of companies will prioritize cybersecurity risk when engaging in business partnerships and third-party transactions in 2025. 

Related: TOP 10 Cyber Security Threats: All You Need to Know

Real-life examples of cybersecurity in various sectors: 

  • Protect personal information with data encryption. Data encryption converts confidential information into complex code that can only be decoded with the right encryption key. This protects user data and prevents hackers from accessing information in case of a breach. 
  • Using MFA to prevent unauthorized access. Multi-factor authentication is a security feature that requires users to provide several verification forms before they can access their accounts. In this case, a hacker can’t access any information even if they get the user’s password. They’ll still need to get a verification code, like a text message. 
  • Physical security. Companies use physical security measures like alarms, system locks, data-destruction systems, etc. to protect their IT infrastructure. 
  • Cybersecurity protects users and companies from cyber attacks
  • Prevents financial losses caused by data breaches
  • Compliance with regulations to prevent legal consequences
  • Cybersecurity isn’t foolproof, so it may provide a false sense of security
  • May be complex for non-tech savvies
  • Cybersecurity is costly

10. Low-code and no-code (LCNC) platforms

Another emerging technology making waves and now becoming a must-have for companies is low-code and no-code solutions.

These tools allow people with little or no knowledge of coding to create and deploy applications, drastically reducing development time.

Companies now use tools like Bubble and Microsoft Power Apps to create apps. This helps them to prototype and deploy effective solutions quickly. 

Interestingly, four of every five U.S. companies now use low-code or no-code platforms to automate their business and app development. 

Real-life examples of low-code and no-code platforms in various sectors: 

  • Helpdesk and self-service portal. Thanks to the self-service portal low-code platforms offer, customers can now benefit from a seamless and intelligent experience. 
  • Inventory management. Retailers use low-code and no-code solutions to manage stock levels, automate inventory tracking, and reorder processes effectively. 
  • Manufacturing. Most manufacturing companies usually have issues sharing data and collaboration because their legacy systems may not integrate well with other core systems. But LCNC applications can resolve this problem by connecting systems, breaking down information silos, and more. 
  • LCNC increases the development speed
  • Offers more flexibility and customization
  • More control over the process of development
  • No coding required
  • Users may still need some coding knowledge
  • May not be ideal for highly complex projects
  • Relies on platform provider for support and updates
  • Customization options may be limited

The Latest Technologies in the Software Industry: Overview 2024

The Latest Technologies in the Software Industry: Overview 2024

Will Artificial Intelligence Take Away Jobs?

Are we going to lose our jobs? The World Economic Forum believes that AI and emerging software development trends will positively impact the job market. 

It’s projected that AI will create 70 million jobs and displace 20 million. 

A 2023 LinkedIn US Executive Confidence Index Survey shows that 47% of executives believe AI will boost productivity, and 40% view AI as the jackpot for growth and revenue. 

However, these statistics seem to focus on corporations, not entirely on employees. 

Of course, Microsoft’s 2023 Work Trend Index reveals that 70% of employees will delegate their tasks to AI to reduce their workloads. I’m assuming these employees are not affected by the job displacement. There are numerous stories of AI driving more layoffs.

What is certain is that there will be a lot of training and re-skilling and some layoffs to enhance other jobs. 

Whether you lose your job will depend on how fast you can adapt to the changing times. At the end of the day, it’s all up to you.


I’ve detailed the emerging technology that is shaping tomorrow’s world. It’s essential to stay current with these technologies to know which skills you may need tomorrow to secure a safe and better job.

Artificial intelligence will keep growing, and the growth speed is so astounding that no one knows what the future will be. But at least you have a fair idea of what’s coming.

ColdFusion offers a detailed guide on how AI started and how it’s going on his YouTube channel. Check it out if you’re interested in what’s happening in the AI world. I know I did! 

If this article was helpful, please share it with your friends and let us know your thoughts in the comments below! Thanks for reading!