From the fleet of self-driving vehicles to extraordinary processing power, Artificial Intelligence has made its way to every industry and operation. However, the extensive hype has even enabled some organizations that are not so familiar with the tech or are working without any thorough research are likely to lose sight of opportunities AI could drive.
Though AI isn’t new, the concept still requires an intelligent approach to innovation. Ideally, the objective behind artificial intelligence was to encapsulate learning and human intelligence so precisely that machines could be enabled to simulate them. However, the race to create AI solutions that can meet business objectives has somewhat made its true purpose of improving human lives take the backseat.
Nevertheless, the introduction of optical pattern recognition, speech and picture manipulation, self-driving cars, language translation, etc. are some of the technologies that have boosted innovation, interest, and of course research.
And therefore, the tech leaders have all the sight at what AI could do for them as the reports have suggested that “the market size of AI is gaining momentum. Gartner predicts AI software will reach $62 billion in 2022 alone, an increase of 21.3% from 2021.”
Since we at BugRaptors have been associated with quality assurance services for a long time, it would be nothing wrong to say that AI has all the potential to leverage efficiency, cost saving, and market share for tech brands. In this blog, we will aim at underlining the potential of AI as a technology that could impart to the digital world. Besides, it will even shed some light on essentials that can help create more successful AI initiatives.
AI & Intelligent Empowerment
The subject of using AI is not limited to machines replacing humans. Rather it is an approach that is meant to nurture more compelling opportunities through an environment where humans and machines co-exist which is actually the true meaning of Intelligent empowerment.
However, it is vital for tech enthusiasts as well as other people to understand that Intelligent Empowerment might sound similar to AI, but the two terms are different. While AI is meant to harness the power of computers for working on tasks that were originally worked by humans to add speed, Intelligent empowerment draws a line when it comes to replacing humans with machines.
In reality, intelligent empowerment is meant to help people achieve precision and make better decisions by using tools that can augment human capability. Intelligent empowerment therefore reduces or eliminates the most consuming and boring tasks that humans are supposed to do. This instead helps to add value to creativity and imagination in more fulfilling tasks.
Besides, there is a massive amount of computing power available on-demand allied to machine learning algorithms that are based on real-time digital data. Such initiatives make way for more and more enterprises to adopt intelligent empowerment. For instance, the potential of ML systems learning from examples could be used to program the exact behavior of the systems, given proper training of the machines is done.
Some of the most amazing examples of such technologies could be seen in self-driving cars, medical imaging, and NLPs. However, these trends have shown the complexities involved related to data availability, formatting of the data, and all the subjects that train the systems successfully.
This leads to the question that what type of tasks are most appropriate for tech? In a broader perspective, the machines pertaining to AI could support more successful work, if the below-mentioned conditions are confirmed to be true and followed:
There is an ample amount of data available that can aid the data-driven processes
The AI-powered machines are constantly monitored by humans recording data in the form of texts, speech, or images.
And if these conditions are met, there are so many routine tasks right from email management to data analysis that could be managed, freeing up people from complex tasks while allowing them to focus on more creative tasks.
All in all, the concept of Intelligent Empowerment is more than just replacing humans with machines but instead leveraging the best of both worlds. While machines can be harnessed for great computational power while human expertise could enable more refined applications of the technology.
For instance, machine learning models made to complement the supply chain could help address any disruptions by allowing humans to have a holistic view of the supply chain and adding to productivity. Such an improvement is therefore achieved with the help of mathematical modeling of business objectives and overcoming any constraints using AI.
Another potential example of leveraging intelligent empowerment could be through innovative services. It can be the deployment of chatbots that can help assist people at airports, and train stations, and guide people across cities. Such efforts are already helping economies and modern enterprises to save more time, improve lifestyle, the work conditions, and thus achieve more continuity in operations without human intervention.
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Intelligent Empowerment, AI, & The Future
Advanced AI and machine learning systems have certain limitations bound to them. For instance, establishing any system requires access to specific computing resources and effective retraining of the data. Moreover, the machine’s ability to make quality decisions entirely depends on the quantity and quality of data used during training. Therefore, it is necessary that any experiment made must be done after mindful research of limitations and then pour the investments in the right direction.
Besides, the ability of developers to identify use cases for intelligent empowerment requires extensive focus and of course, a little space for disappointment when performing AI testing. However, having a little sense of direction could help meet the ambitions and work on a roadmap that can create value.
Driving Intelligent Empowerment As A Company
To innovate on intelligent empowerment as an organization is entirely a matter of data. Right from defining the data strategy to the selection of sources and data owners, the quality of information is a constant factor. Besides, it is necessary that sources and data owners should all understand the objective of the technology and the needs of the end users while keeping in agreement with the confidentiality goals.
Apart from this, it is necessary that the requirement for an enterprise-wide data platform should be recognized at the earliest to allow effective collection, management, and storage of the data. Be it developing the design of APIs or creating data lakes and using of cloud, everything should be considered well in time.
On top of that, there are so many other important factors that need careful analysis and interpretation before deployment is done. This includes strengthening data science skills, finding the most reliable team of data scientists, data analytics, and of course reliable application of machine learning algorithms.
Once done, you can straight away head for data evaluation, visualization, decision preparation, and everything that can help create adaptive AI solutions. With a careful effort made towards quality assurance services, the enterprises could reinforce all their actions on creating faster and more efficient decisions.
All in all, the original idea behind intelligent empowerment is only about creating technologies that can release humans from simple yet cumbersome tasks while creating a space for innovation and creativity. And just in case you need some assistance meeting your tech goals, we can help you with everything that you need to meet the digital transformation goals.
Reach our experts to learn about the wide range of AI & ML testing services we bring to you.
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