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Adapting your business digital strategies in 2024 with more AI

AI is revolutionizing the way businesses operate in today’s digital age. 2023 was all about harnessing the power of artificial intelligence to drive corporate success. By integrating AI into their digital strategies, companies could unlock a multitude of benefits that help them stay ahead of the competition and drive success, even in uncertain times. From e-commerce giants to small online startups, it became an integral part of businesses across industries. So, if you want your business to thrive in 2024 and beyond, it’s time to adapt your digital strategies and embrace the AI revolution.

AI refers to the development of computer systems that can perform tasks that typically require human intelligence. These intelligent machines have the power to analyze vast amounts of data, learn from patterns and trends, and make informed decisions. One key role of AI in business is automation. With its ability to handle repetitive and mundane tasks, AI frees up valuable time for employees to focus on more strategic initiatives. From customer service chatbots providing instant assistance to automated inventory management systems optimizing supply chains, AI streamlines operations and boosts efficiency.

 

Another vital aspect is predictive analytics powered by ML algorithms. By analyzing historical data, AI systems can identify patterns and predict future outcomes with remarkable accuracy. This allows businesses to make data-driven decisions, optimize marketing campaigns based on consumer behavior analysis, personalize user experiences on e-commerce platforms, and even forecast demand for products or services.

 

Moreover, AI enables personalized recommendations tailored specifically for each customer. By understanding their preferences through behavioral analysis or purchase history examination, businesses can offer relevant product suggestions that enhance engagement and drive sales.

 

The role of AI extends beyond operational efficiency; it also revolutionizes decision-making processes within organizations. Through advanced algorithms and natural language processing capabilities, AI helps executives access real-time insights from multiple sources at lightning speed. This empowers them to make well-informed decisions swiftly – a competitive advantage in today’s fast-paced business environment.

 

Embracing the role of AI in your business strategies opens doors to endless possibilities for growth and innovation while improving operational efficiency across various departments. As we delve deeper into this exciting topic in this blog post, you’ll find practical examples from successful implementations around the globe!

 

Examples of Successful AI Integration in Businesses

 

AI integration has revolutionized various industries, enabling businesses to streamline their operations and enhance customer experiences.

In the retail sector, companies like Amazon have leveraged AI algorithms to personalize product recommendations for customers based on their browsing and purchase history. This not only improves customer satisfaction but also boosts sales by driving targeted marketing efforts.

 

AI-powered chatbots have become increasingly popular in the customer service industry. Companies such as Amazon, Bol, have implemented chatbots that can handle basic customer inquiries, reducing response times and improving efficiency.

 

The healthcare industry has also seen significant advancements with AI integration. For instance, IBM’s Watson Health platform utilizes AI technology to analyze vast amounts of medical data, assisting doctors in diagnosing diseases more accurately and efficiently.

 

In the manufacturing sector, companies like Tesla have embraced AI-driven automation systems to optimize production processes. These intelligent machines can monitor quality control, predict machinery maintenance needs, and increase overall productivity.

 

E-commerce giants like Alibaba are utilizing AI algorithms to analyze consumer behavior patterns and make real-time pricing adjustments accordingly. This allows them to offer personalized promotions tailored specifically to individual customers’ preferences.

 

These examples demonstrate how successful implementation of AI technologies can drive growth, improve operational efficiency, enhance customer experiences, and ultimately lead businesses toward success in today’s digital age.

 

How to Prepare Your Business for the Inevitable Shift towards AI

 

As technology continues to advance at a rapid pace, it’s becoming increasingly clear that AI will continue to play a crucial role in shaping the future of businesses. To stay ahead in this digital age, companies need to start preparing themselves for the inevitable shift towards AI.

 

One way to prepare your business for this shift is by investing in AI-powered tools and software. These tools can help automate repetitive tasks, analyze large amounts of data, and provide valuable insights that can inform decision-making processes. By leveraging these capabilities, businesses can optimize their operations and improve overall efficiency.

 

Another important aspect of preparing your business for AI is upskilling your workforce. As AI becomes more prevalent in the workplace, employees will need to acquire new skills and adapt to working alongside intelligent machines. Providing training programs and educational resources can help employees embrace AI technology and use it effectively within their roles.

 

Additionally, businesses should also focus on building a strong data infrastructure. With AI relying heavily on data analysis, having clean and reliable data sets is essential for accurate predictions and insights. Implementing robust data management systems can ensure that you have access to high-quality data that fuels your AI initiatives.

 

Furthermore, fostering an innovative culture within your organization can greatly facilitate the adoption of AI technologies. Encouraging experimentation with new ideas and providing avenues for collaboration between different teams can lead to breakthroughs in implementing AI solutions tailored specifically to your business needs.

 

Staying informed about industry trends related to AI is vital for any business looking to thrive in the digital landscape. Keeping abreast of advancements in machine learning algorithms or emerging applications of AI can give you a competitive edge over others who may be slower to adopt these technologies.

 

Therefore, businesses must recognize the transformative power of AI as they plan their strategies moving forward into 2024 and beyond. By taking proactive steps such as investing in AI tools, upskilling employees, focusing on data infrastructure, fostering innovation, and staying informed about AI trends, businesses can position themselves in a powerful position.

What is Generative AI & how it’s transforming the Software and Tech Ecosystem

Artificial intelligence is one of the most disruptive technologies of our time. It has revolutionized many industries, from healthcare to finance and beyond. However, it’s not just limited to that – the emergence of generative AI has opened up new possibilities for software and tech innovation.

 

Generative AI, or Generative Artificial Intelligence, refers to a field of AI that focuses on creating or generating new content, such as images, text, audio, or even video, using machine learning techniques. It involves training models to understand patterns and structures in existing data and then using that knowledge to generate new, original content that resembles the training data. Unlike traditional AI models, generative AI can produce original and unique output without human intervention, making it highly valuable in various fields. Generative AI has been transforming the software and tech ecosystem in several ways:

 

Content Generation: Generative AI enables the automatic creation of realistic and high-quality content. For example, it can generate realistic images of nonexistent objects or landscapes, produce coherent and contextually relevant text, compose original music, or even create deepfake videos. Generative AI algorithms can create new pieces of content by learning patterns from existing data, making it easier for businesses to generate creative outputs.This technology has the potential to revolutionize various creative industries such as advertising, design, entertainment, and art.

 

Personalization and Recommendation Systems: Generative AI helps in building more personalized and effective recommendation systems. By understanding user preferences and generating tailored recommendations, it enhances user experiences across various platforms, including e-commerce, streaming services, social media, and news platforms.

 

Simulation and Training: Generative AI allows for the creation of realistic simulations and training environments. This has applications in fields like autonomous vehicles, robotics, and healthcare, where virtual simulations can be used to train and test systems without the need for real-world deployment. It also aids in training models for reinforcement learning by generating diverse and challenging scenarios.

 

Data Augmentation: Generative AI can be used to augment existing datasets, especially when data availability is limited. It can generate synthetic data that resembles real data, helping to improve the performance and robustness of machine learning models. This is particularly useful in domains such as medical imaging, where acquiring large labeled datasets can be challenging.

 

Creativity and Design: Generative AI provides new tools for creative professionals by automating certain aspects of the design process. It can generate design suggestions, assist in creating artwork, generate variations of designs, or aid in prototyping and iteration. This empowers designers to explore larger design space and enhances their creative workflows.

 

Generative AI is a game-changing technology that has the potential to revolutionize various industries. From creating realistic synthetic images and videos to aiding in drug discovery, Generative AI is transforming the software and tech ecosystem in unprecedented ways. The ability of Generative AI to generate new ideas, designs, and solutions could lead to groundbreaking innovations that can help solve some of our most pressing problems.

 

However, the advancement of generative AI also brings challenges and ethical considerations. Issues such as authenticity, copyright infringement, misinformation, and the potential for misuse of generated content need to be addressed. It is crucial to develop responsible frameworks and guidelines to ensure the ethical and safe deployment of generative AI technologies. Its applications have the potential to reshape various industries and user experiences, but ethical considerations must accompany its development and deployment.

 

How IOT can improve the Project Management Process

The world of project management is rapidly evolving, and with the emergence of Internet of Things (IoT) technology, managing projects has become even more efficient. IoT has opened up a whole new world of possibilities for project managers who are looking to improve their processes and enhance productivity. IoT has the potential to significantly enhance the project management process by providing real-time data, improving communication and collaboration, optimizing resource allocation, and enabling proactive decision-making. Here are several ways in which IoT can improve project management:

IoT can be a game-changer in project management by allowing real-time data collection and monitoring of various aspects of a project. For example, IoT devices, such as sensors and connected equipment, can gather real-time data on various project parameters, including progress, performance, environmental conditions, and resource utilization. This data can be automatically transmitted to project management systems, providing up-to-date insights that enable better monitoring, tracking, and decision-making.

 

IoT devices also allow project managers to remotely monitor project sites, equipment, and assets in real-time. Through connected cameras, sensors, and wearables, project managers can assess on-site conditions, detect potential issues or delays, and ensure compliance with safety protocols. This capability improves efficiency and reduces the need for physical presence at project locations. Thus, managers can easily access data on from any remote location to monitor performance metrics in real time.

 

In addition, IoT sensors embedded in equipment, machinery, and vehicles can collect data on their usage, performance, and maintenance needs. By analyzing this data, project managers can optimize resource allocation, schedule preventive maintenance, and reduce downtime. This ensures that resources are utilized efficiently, delays are minimized, and costs are optimized.

 

Another benefit of using IoT in project management is its ability to automate routine tasks through machine learning algorithms. These algorithms analyze large amounts of data generated from sensors and make predictions based on patterns identified over time.

 

Furthermore, IoT enables better communication among team members by providing a centralized platform for sharing information and updates. This leads to increased collaboration, as everyone has access to the same data and insights. IoT helps reduce costs associated with traditional project management methods by eliminating unnecessary paperwork and travel expenses. With everything managed digitally through connected devices, there are fewer physical resources required overall. Incorporating IoT into your project management process offers many valuable benefits that ultimately lead to smoother operations and successful outcomes.

 

Another benefit of IoT in project management is improved efficiency. By automating certain tasks with smart devices like sensors or drones, teams can save time and focus on more important aspects of the project. Additionally, data collected from these devices can be used to identify areas where improvements could be made further down the line

 

Conclusion

 

The Internet of Things (IoT) is a game-changer in project management. It is widely expected that the adoption of IoT will continue to grow across industries as more companies recognize its potential and benefits. The IoT market has been expanding rapidly in recent years, with a wide range of organizations implementing IoT solutions to improve their operations, enhance customer experiences, and drive innovation.

By leveraging the power of IoT, project managers can gain real-time insights, improve decision-making, optimize resource allocation, enhance collaboration, and mitigate risks. However, successful implementation requires careful planning, integration with project management systems, data security considerations, and a clear understanding of the specific project requirements and objectives.

The future of project management lies with IoT integration as it enables seamless collaboration among team members regardless of location or time zone. With proper utilization of this technology, businesses will achieve optimal performance levels leading to successful completion of projects within set timelines and budgets.

How machine learning and artificial intelligence are changing RPA’s Landscape

Robotic Process Automation (RPA) is a technology that allows software robots to automate repetitive and rule-based tasks, such as data entry, processing transactions, and generating reports. The integration of ML and AI with RPA has taken the industry by storm. This dynamic combination is revolutionizing the way businesses operate, making processes faster and more efficient than ever before. ML & AI are being used in RPA to streamline processes to reduce costs, increase productivity, enhance RPA’s capabilities, and enable it to perform more complex tasks.

There are diverse types of RPA solutions available on the market, each with its own unique capabilities. Below are some of the most popular RPA solutions and their capabilities:

 

  • Automation Anywhere: Offers both web-based and desktop-based bots. Capabilities include screen scraping, data manipulation, file transfer, workflow automation, etc.
  • Blue Prism: Provides desktop-based bots that can be deployed on-premises or in the cloud. Capabilities include process mining, exception handling, automatic documentation generation, etc.
  • UiPath: Offers both web-based and desktop-based bots. Capabilities include image recognition, natural language processing (NLP), process mining, etc.

 

How machine learning and artificial intelligence are boosting RPA

 

The use of ML and AI is helping to boost the capabilities of RPA, with both technologies working together to automate a wide range of processes. ML is being used to develop bots that can understand and respond to human interaction, making them more natural and efficient communicators. This is particularly useful in customer service applications, where bots can handle large volumes of inquiries without getting overwhelmed.

AI, on the other hand, is being used to create bots that can think for themselves and make decisions on their own. This is proving invaluable in more complex processes where humans may struggle to keep up with the pace. AI-powered bots can identify patterns and exceptions, meaning they can often solve problems faster and more effectively than their human counterparts.

With ML and AI capabilities, RPA bots can make more intelligent decisions based on data analysis, predictive analytics, and other advanced techniques. This can enable them to handle more complex tasks and make better recommendations. ML and AI can also help RPA bots to scale more effectively. This is particularly useful in high-volume environments where there is a need for rapid processing and analysis.

How to get started with machine learning and artificial intelligence in your RPA process

 

Machine learning and artificial intelligence are increasingly becoming essential components of RPA, enabling robots to learn from their mistakes and become more efficient as they process data. If you’re looking to get started with machine learning and artificial intelligence in your RPA process, there are a few things you need to do.

First, you need to identify what tasks in your process can be automated using ML & AI. You must also define the business problem you want to solve using ML and AI in your RPA process. This could be a task that requires more intelligence and decision-making than your current RPA bots can handle. Once you’ve identified those tasks, you need to find the right software solution that can help you automate them.

 

Also, to use ML and AI in your RPA process, you will need data to train your algorithms. Identify the data you need and where you can obtain it. There are many different ML algorithms to choose from, so choose the one that best suits your identified business problem and data. Use that data to train your ML algorithm. This involves feeding your algorithm with labeled data to help it learn and make predictions. Once your ML algorithm is trained, integrate it into your RPA process. This involves connecting your ML algorithm to your RPA bots and using it to automate more complex tasks.

Finally, you need to implement the automation solution and monitor its performance over time and refine it as necessary. ML and AI can help you automate more complex tasks if you continuously evaluate your RPA process and look for opportunities to improve efficiency, accuracy, and productivity. By following these steps, you can ensure that ML and AI will play a positive role in your RPA process.

 

Below are some examples of how ML & AI can be used in RPA:

  • Natural Language Processing: NLP is used to extract and process data from unstructured text, such as emails and chat logs. RPA bots can use NLP to understand the intent of a user’s message and take appropriate actions based on the context.
  • Computer Vision: Computer vision can be used to enable RPA bots to read and interpret images, such as screenshots of a user interface or a scanned document. This can be useful in automating tasks such as data entry and document processing.
  • Predictive Analytics: ML algorithms can be used to analyze data and identify patterns that can help RPA bots make predictions and decisions. For example, an RPA bot could use predictive analytics to identify customers who are likely to churn and take proactive measures to retain them.
  • Reinforcement Learning: Reinforcement learning can be used to train RPA bots to learn from their actions and improve their performance over time. This can be useful in tasks such as fraud detection, where the bot can learn from its mistakes and improve its accuracy over time.

 

With these examples in mind, it is clear that machine learning and AI will continue to play a key role in driving further innovation in the world of RPA. Remember that implementing ML and AI in your RPA process requires a solid understanding of both technologies. If you do not have the necessary skills in-house, consider contacting us to ensure that you will get the most out of your investment.

Accelerated Automation: RPA as a Service (RPAaaS)

RPA – Robotic Process Automation – is the automated processing of business processes by digital software robots. This technology beings its support in clearly structured, repetitive, and rule-based processes and tasks that are carried out by people. With RPA, companies can implement a level of precision in the processing of tasks that is often unattainable by human alone. In this robot-controlled process automation, the bots take over the roles and tasks of users and interact with other software systems. Almost half of all processes in companies can be automated with the help of RPA.

 

RPA as a Service is the easiest and fastest way to use the advantages of Robotic Process Automation (RPA). RPA as a service means companies can take advantage of the many benefits of RPA without the upfront cost, inconvenience, and maintenance of buying their own RPA technology or hiring in-house RPA developers. RPAaaS offers a selection of out-of-the-box RPA services and tools accessible through a monthly subscription in order to meet the needs of every business for quick and cost-effective intelligent automation.

Accelerated Automation RPA as a Service RPAaaS
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Every organization has different needs, timelines, and budgets, therefore, RPAaaS solves the problem of a lack of in-house development resources not only by providing the development platform but also by offering bookable, qualified RPA experts, such as, RPA business analysts, RPA developers, or RPA architects. Thanks to the model of resources that can be booked as required, load peaks can be flexibly balanced and the schedules for scaling bots can adhere. The main objective of RPAaaS is to reduce development and deployment costs and quickly and effectively meet the need for effective and reusable automation components.

 

The relocation of automation assets to the cloud opens up a way for financially constrained companies to tackle the planned business process automation or to scale existing automation approaches without having to hire qualified automation personnel and also by eliminating the need for infrastructure and maintenance.

 

Business continuity, supporting a distributed workforce or digital transformation, whatever the business goal is, with RPA as a service, a company does not need to purchase its own servers, licenses, or professional services. RPAaaS is therefore also suitable for companies that only plan to use it for a limited period of time. Because in this case, there is no point in purchasing expensive RPA technology that will no longer be used after a certain project has been completed.

Hyper-automation: The Future of Digital Transformation

When it comes to digitization processes in companies, there is more and more talk of hyper-automation. But what is it actually? For some it is just a comprehensive form of process optimization; for others, hyper-automation is the future strategic technology that is not to be ignored.

“Hyperautomation has shifted from an option to a condition of survival,” said Fabrizio Biscotti, research vice president at Gartner. “Organizations will require more IT and business process automation as they are forced to accelerate digital transformation plans in a post-COVID-19, digital-first world.”

 

Hyperautomation The Future of Digital Transformation

 

What actually is hyper-automation?

The term hyper-automation goes back to the market research company Gartner. This means a well-founded methodology for achieving tactical and strategic goals through the automation of business processes. Thus, Hyperautomation considers the automation of business processes on a large scale by combining a wide range of coordinated digital technologies.

According to Gartner, hyper-automation focuses on two aspects of business operations: The first is to automate whatever can be automated within an organization. The second is to combine different approaches, tools, and technologies to automate only individual tasks (RPA) but also complex processes with the help of artificial intelligence (AI), virtual assistants, and machine learning (ML).

 

How does hyper-automation work?

Hyperautomation is able to unlock maximum potential by combining a number of technologies that support each other and automate complex processes with unstructured data and a significant level of ambiguity. By using AI, ML, NLP, process mining, and intelligent technologies, the ability to discover processes independently is enhanced, and RPA bots are enabled to do much more than just perform the previous repetitive tasks.

Basically, hyper-automation takes on another level of human work. It’s not only a tool but a unified enterprise strategy or initiative with the ultimate goal of creating and optimizing end-to-end processes to achieve an even higher degree of automation that supports innovative new business propositions.

Hyperautomation only works if bots ultimately also perform the tasks that a machine learning (AI) has identified. Advanced artificial intelligence can better analyze unstructured data and implant it in an efficient workflow. With RPA being the fundamental part of hyper-automation, intelligent bots continue to process the data in hyper-automation and ultimately ensure that the work is done.

 

Benefits of hyper-automation

As already described, hyper-automation enables automation that goes beyond simple, repetitive process sections. With hyper-automation, comprehensive automation can cover even complex processes. Reducing costs and maximizing profits, but also conserving resources and designing a smart working environment are also considered as main benefits. When used correctly, hyper-automation leads to a higher degree of automation and higher productivity in the company. A significant increase in customer satisfaction can also be achieved by integrating the personalized customer service. The side-by-side collaboration of man and machine is the ultimate goal of hyper-automation.

 

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Smart companies: Tips for a smooth integration of AI

AI (Artificial Intelligence) has a long history of being considered science fiction but opens up enormous potential for companies in terms of productivity, the efficiency of business processes, gain sustainable competitive advantage and customer relationships. Covid-19 pandemic is the proof of accelerated use of AI across multiple industries around the globe.

Smart companies Tips for a smooth integration of AI

According to the latest title “Global Artificial Intelligence Market” published by Facts & Factors, the global Artificial Intelligence market size is expected to reach USD 299.64 Billion by 2026 from USD 29.86 Billion in 2020, at a compound annual growth rate (CAGR) of 35.6% during the forecast period 2021 to 2026.

Most companies believe that AI is certainly one of the foremost technologies of the future even though they still aren’t making the most out of their relationship with AI. Here below are few obstacles to AI adoption and how they can be avoided.

 

The Preparation Phase

For many people, there is still something mystical or threatening about AI. Although intelligent technologies act invisibly in our everyday life, the image of AI often emerges as futuristic, emotionless robots that look amazingly like Arnold Schwarzenegger are going to hunt us down and kill us. But AI is only aimed to develop machines/computers that are capable of doing things normally done by people. The lack of knowledge is one of the main obstacles to AI adoption. The implementation of new technologies should always be seen as a long-term project. As there really isn’t a textbook on how to adopt AI at the enterprise level, people with the right mindset need to be brought into an organization to help facilitate changes and capitalize on opportunities.

In many cases, high costs and a lack of resources are also decisive obstacles. But not every company directly needs its own computing resources or expensive, in-house developed platforms. In many cases, it’s worth taking a look at third-party AI platforms or in the public cloud. They enable the use of powerful and scalable AI solutions without the need for extensive investments of your own. The experience of the major platform providers also helps to implement projects as quickly as possible.

 

Communication is the key

The challenge of scaling AI and automation often does not lie in the technology itself. Rather, the corporate culture is often important in order to implement changes in the work environment. Thus, before the introduction of the AI, timely communication with employees is essential. The benefits of AI must be well elaborated and appropriate training must be planned for all employees. Artificial intelligence requires specialists who are well educated and have to be trained. This is the only way to develop, operate and maintain intelligent systems and to handle advanced troubleshooting and continuous improvement of these solutions. Tasks and responsibilities transformation must also be openly discussed to deal with the fear of losing jobs among employees, as, AI will complement rather than replace employees.

 

Introduction of a clear AI strategy

Small and medium-sized companies, in particular, are often reluctant to implement AI because they lack a clear strategy. In the first step, however, a fully developed strategy is not absolutely necessary: ​​rather it is more important for companies to understand the technology and recognize the possibilities it offers. At this point, experts should be consulted to elaborate on the benefits of AI and how can this actually benefit the company? What are the installation process and its duration? What type of data or tools are needed to work successfully?  What can be done to achieve results? Once all questions are clarified, and a strategy has been worked out the introduction can be prepared.

 

AI technical requirements

Like a human, an AI system also needs time to learn. That is why it takes time for the first successes to be measurable. In order to have a decisive influence on the development of companies, good implementation is requisite. The AI requires various available data that it can analyze. This is the only way to generate data models that can be used as a basis for future predictions or decisions. The implementation effort depends, among other things, on the flexibility of the software that a company uses. Another factor is the specific use cases that should be automated with the help of AI and that must be taken into account as early as the implementation phase. It is possible to start individually with each communication channel, regardless of whether it is email, chat or telephone. Preferably, however, the channels are placed one after the other. As a result, a company does not lose any time, because the advantages of an omnichannel system are that the training results of one channel flow into the learning process of the other channels. Depending on the use case, the AI ​​applies different algorithms and develops certain models. The learning is based on the trial-and-error method until it has developed the right model.

 

The AI ​​promises long-term optimization in terms of profitability and efficiency of in-house processes. With the ability of self-learning, algorithms can be used to improve existing processes and products as well as develop new business models. This means that AI has the potential to change entire industries and value chains over the long term. Artificial intelligence also opens up cross-sector value creation opportunities and growth potential for small and medium-sized companies. To gain all benefits related to AI, the first step is the will to deal with the topic of AI and ultimately its implementation. Therefore a well-developed strategy is required.

 

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Automation myths debunked: Why is Automation important for your business?

Hardly any company that strategically pursues their company growth can get around automation today. Automation enables tasks that were previously slow, manual, old-fashioned, and time-consuming to be supported with suitable software and thus run independently. As a human error can be unpredictable and happen when you least expect it, with the right technology companies’ processes are more accurate and faster. Use cases of automation are, for example, employee onboarding, analyzing reports on transactions, monitoring bookkeeping activities regularly, customer service, databases updates, sending personalized emails, perform inventory, etc.

Business processes automation can not only be used to gain efficiency. Availability of modern technology, as well as enhanced software applications, have made it easier to increase employee efficiency and you can get better results when you embrace automation. A win-win situation for companies and employees.

 

But despite these benefits, there are still myths surrounding automation that keep companies from getting started. Even though automated processes create positive changes, still, many companies fear high costs, difficult implementation, and staff changes – but these are just prejudices that we would like to address here and thus show that every company can benefit from automation.

 

Automation is a complicated and complex process

Hmmm, yeah. Not if it’s done right. As is often the case, good preparation is half the work. So, before starting with automation, make sure you understand what your company’s expectations are. Your decision to automate must depend on your needs, capacity to build it, and also your customers’ requirements. Specific goals can be developed using your personal business case. This step is essential so that automation succeeds and creates benefits for the company.

These requirements should also be discussed in-depth with different automation tool providers instead of falling for fancy advertising promises or the cheapest subscription. It is advised to meet with different process automation providers for not only choosing the right tool, but also to evaluate your own requirements.

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The future is automated

‍Automated processes bring a lot of advantages in operational processes, such as improved operational efficiency, long-term cost reduction, better customer service, visibility & transparency, and an increase in productivity. However, if a company only carries a small range of products, stores a manageable amount of goods, and generally only offers a small storage capacity, there is no need to implement a fully automated system. In such cases, manual or partially automated solutions that grow with you are the better options. Companies then have to weigh up whether small order quantities can be processed more efficiently in this way.

 

Automation is killing jobs

Nowadays it is constantly stated that automation is accompanied by a huge burden of unemployment. With the increased use of machines and automated processes, the fear of reducing or replacing staff increases. It’s true that automation is impacting various jobs in different sectors around the world. Due to automation, human intervention is certainly reduced in a business process. For instance, from production to planning, everything can be controlled by artificial intelligence or machine intelligence. It is easier to bring accuracy into the production process and increase overall productivity with machine intelligence. Every company wants to reduce the number of its employees as much as possible through technological improvements. But that does not mean that we are heading towards an unemployed society in years to come. As the machines are performing tasks previously done by humans, companies are busy transforming and redesigning jobs in a way that can make technological elements compatible with human capital development. The future workplace is where humans and machines will enhance each other’s strengths by working side by side.

 

Existing systems prevent the integration of new solutions

Automation doesn’t happen overnight – Companies are constantly faced with the challenge of proper integration of a set of services related to automation and ensuring that all expectations are aligned with business goals. Integrating your automation initiatives successfully is impossible without a flexible, scalable infrastructure. Therefore, on-premise infrastructure must be avoided/limited because of its limitation in terms of automation roll-out, scalability, and ease of use. For this purpose, cloud solutions are ideal as they let you get straight to work without wasting your valuable time on on-premise setup and maintenance.

 

So, now that you know that automation is here to stay, and can help you better run your business, it’s a safe bet that such automation can be trusted and utilized. By taking into account the myths discussed in this article, and learning the truth about each, you’ll be able to run your business more effectively.

Business Process Automation Trends 2021

As 2020 is slowly drawing to a close, it is time to discuss future trends in (industrial) automation that are likely to have a significant impact in 2021. Based on the current facts, conclusions can be drawn that artificial intelligence and automation will bring steady innovation for companies of all sizes and from all sectors. During 2020, automation technologies have experienced a substantial boom especially due to the covid19 pandemic. Industrial and manufacturing operations have been massively evolved with the integration of machine learning and robotics. In fact, companies and industries are no longer fully dependent on a human workforce for simple, complex, manual, and repetitive tasks. They are gaining a competitive advantage with digitalization and IoT.

Here below are the top emerging trends to watch in automation for upcoming years:

 

  • RPA and business workflows

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RPA isn’t new, many companies use this technology to automate their routine tasks. RPA as an industry is growing exponentially– the global robotic process automation market size is expected to reach USD 10.7 billion by 2027, expanding at a CAGR of 33.6% from 2020 to 2027 – Grand View Research. RPA used in the automation of manual and low-value repetitive tasks, such as data entry (order, invoice, etc), looking up information in databases, typing in updates, prepare a template, run and download reports, read and reply email, send emails to follow up with customers, etc. is passed. During the pandemic, organizations realized their technological backwardness and the risks associated with a further delay in digitization.

In 2021 everything will revolve around business workflows. The call for digital transformation is growing and ensuring streamlined, smooth processes that delight both customers and employees. To achieve this, companies are increasingly targeting intelligent RPA solutions. Because many processes in companies are still only partially automated – if at all. It will therefore be about making RPA technology even better usable in the future. With the integration of Cognitive RPA along with other intelligent components, business processes that require human reasoning or decision-making can be automated.  A robot cannot, therefore, decide on its own to add a new dimension to the process that has not been precisely defined before. This is the only way to automate business-critical workflows end-to-end, for example.

 

  • Automation and Cyber-Threat

In order to protect against automated modern cyberattacks, organizations will be incorporating automation into cybersecurity efforts. Automation plays an important role in defense against threats. Modern automatisms will increasingly develop their effect in the fight against the threat by reducing the volume of threats and allowing faster prevention of new and previously unknown threats.

If implemented appropriately, providers of cloud platforms can take action against cybercriminal groups that use trusted services for malicious attacks. In the past, it has been observed how legitimate websites – for example, Microsoft365 or Google Drive – have been imitated in order to steal data entered by unsuspecting victims. With the right tools and validation technologies, automation can aid in the prevention of successful cyberattacks and track down such fake login pages – with the aim of counteracting the risk.

 

  • Digital employees

As the ongoing global pandemic, has triggered an acceleration of a digital working environment, business leaders are learning lessons to apply to their futuristic organizations. Remote work is here to stay; thus, many organizations were forced to tap into their technologies and pushed creative ways of leveraging them to ensure business continuity. Businesses around the globe are exploring how they can implement and strengthen their digital strategies and unleash the true power of Technology – not just from a technology and environment perspective but from leadership, change management, and career-growth perspectives, as well. Companies are preparing themselves for the hybrid future or work by investing heavily in the tools needed to work remotely and prioritizing tech and digital infrastructure investments that support sustainable remote/hybrid work.

While no one knows exactly what the future holds for us, according to Forrester, companies are investing a lot in an “anywhere-plus-office hybrid” model in which more people will work outside the office more of the time. Therefore, it’s certain that remote working will play a major role in how the workplace will evolve in the coming years and will continue changing the way we work.

 

Sources:

COVID19: Home-Office Exposed to Insider Threats

INSIDER THREAT HOME OFFICE COVID 19

 

The world has gone through immense changes in the recent decades. Since the dawn of time, humans have developed tools and technology to achieve their goals. We’ve witnessed large shifts in technology and social structures. Today, technological advances are rapidly making it possible to automate as much as possible of the work currently carried out by humans through robotics, internet of things, machine learning and artificial intelligence. These RPA robots are capable to mimic human user actions. They log into applications, move files and folders, copy and paste data, fill in forms, extract structures and semi-structures data from documents and many more. Companies also have an immense capability to store, process and transmit data, to an extent that traditional paper documents are being replaced by or converted to digital media.

 

With the rise of technology, data breaches and security incidents are coming from all over the digital sphere and are increasingly costly. These cybersecurity threats are impacting companies and organizations on a daily basics. According to a new report from IBM and the Ponemon Institute, the average cost of a data breach in 2020 is $3.86 million. As organizations are busy in defending themselves against external threats, they need to remember that insider threats can also be harmful. Because whether Intentional or not, employees take certain actions that carry a significant impact on an organization’s trustworthiness, data loss, reputation, reliability, safety, and credibility. A situation which isn’t ignorable as now, due to COVID19, more and more people work from home using their own devices to access company resources.

 

In their recent “2020 Insider Threat report” Bitglass, the cloud security provider, has underlined that 61% of those surveyed were exposed to an insider attack in the last 12 months, 22% reported an insider attack in at least past six months. For 49% of respondents, it takes at least one week before they detect an insider attack, and for 44% of them another week or more can go by before they recover from such an attack.

 

Additionally, the year 2020 has brought unexpected changes to the global economy and the world of work. One of the challenges businesses face today is protecting their assets in a virtual environment which are vulnerable to attacks both from inside and out. Organizations are undergoing fundamental changes, including the rapid move to the cloud and widespread adoption of teleworking due to the COVID19 pandemic situation. Teleworking has certainly proven itself an important aspect of ensuring business continuity, but poses a huge challenge on how to prevent cybersecurity threats while workers are working from home, as well as how employers can comply with data protection and privacy regulations, such as the EU General Data Protection Regulation.

 

Home office combined with protecting against insider threats poses greater challenges. 82% of organizations cannot guarantee that they will be able to detect insider threats deriving from employees’ personal, unmanaged, unprotected devices, versus 50% from the cloud, while 81% find it difficult to assess the impact of insider threats. Even before the pandemic, companies had to cope with limited security budgets. And now due to covid circumstance, security teams are obliged to do even more with less. 73% of companies haven’t planned any increase in their security budgets for the coming year instead they are planning a reduction inti.

 

“Companies report that the loss of critical data and business interruption are the worst effects of an insider attack,” said Anurag Kahol, CTO of Bitglass. Organizations need a versatile security platform that enables real time monitoring of user behaviour, protection of personal devices, ensure maximum uptime, achieve cost savings, and prevent data loss associated with interactions. Thus, leaders in all industries must equip their organizations with automated, real-time protection measures to effectively respond to these emerging insider threats.

 

Source:

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