Today’s information age drives large and small companies globally to go digital. Gartner survey for 2017 showed that 42% of CEOs had already begun the digital business transformation, and 56% of them had already raised profits due to improvements. Among their top business priorities for 2017-2018, 31% of the respondents cited IT-related targets.
Digital transformation (DT) has accelerated together with the increasing understanding of its benefits. Companies across various industries implement new technologies into their business processes to organize more efficient management structures, improve engagement with consumers, enhance customer experience and to stay competitive.
The main driving forces of digital transformation are automation and artificial intelligence (AI). Enterprises have been using automation for quite a long time. Initially, it started with machines replacing humans on assembly lines to perform simple repetitive tasks. As artificial intelligence progressed, robotic process automation (RPA) was implemented to carry out high-volume jobs that involve many applications. Today, cognitive algorithms are deployed in the most complicated environments that imitate human reasoning, monitor deviations from norms, warn operators about them and make decisions.
We are witnessing the creation of a new model of working — intelligent automation (IA). It dramatically changes the way humans and machines interact with each other under the rapid growth of data flows, digitization of life and practically unlimited computing power.
Obstacles to Digital Transformation
Integration of digital strategy with legacy systems turned out to be a painful process that requires new thinking and fundamental changes at all levels of a company. Slow digital transformation is a headache for any modern enterprise, as it doesn’t allow getting ahead fast enough to gain the competitive edge. Reality demands dynamism, so business and IT teams should work together under pressure to accelerate the transformation procedures.
Today, there are two serious barriers to dynamic and effective DT.
The Technology Gap
Conventional integration tools are not able to handle today’s development rate, because:
- Departments use hundreds of apps, and integration between them is growing rapidly
- Interconnection must be quick, and changes must be done frequently
- Customer data is splinted like never before, so it may be difficult to support transparency and provide relevant and accurate information
The Social Gap
Business and IT teams within one organization lack cooperation as they are divided. They achieve similar goals by different means. This results in poor visibility, misunderstanding, slower processes and greater risks. To succeed, a company needs both teams working as a unit.
Intelligent automation is the solution to addressing these problems.
What Is Intelligent Automation?
The simplest intelligent automation definition is a combination of automation and artificial intelligence.
One can define intelligent automation in another way: it’s a joint implementation of machines and software intelligence into the production process in order to assist people in creating new products and services.
Gartner defines intelligent automation services as the umbrella term for a variety of strategies, skills, tools and techniques that service providers are using to remove the need for labor and increase the predictability and reliability of services while reducing the cost of delivery.
IA can surmount the following problems:
- High labor cost
- Shortage of workforce
- Inability to process data due to its complexity and volume
- Ineffectiveness of labor
- Bad quality
According to Gartner, IA will alter the provision of managed workplace services over the next few years, increasing service quality at a lower price. Management leaders must prepare to restructure these services and renegotiate contracts to leverage intelligent automation.
The fundamentals of IA implementation include a knowledge base, governance, an apt toolset, analytics, continuous improvement and a solid IT environment. A company can effectively use IA only if it has a mature management system and a definitive planning methodology.
IA in Practice
Intelligent automation systems can be implemented in nearly every industrial sector. They not only process vast amounts of information, but also analyze data, spot inconsistencies, check for correctness, learn in the process of work, adapt to changes and make decisions. Though the final confirmation still depends on a human operator, much of the work is done by the intelligent automation software, resulting in time-saving.
Advanced techniques and great computing power create a new generation of hardware and software robots that perform both cognitive and physical tasks. Multiple intelligent automation examples can be found in various fields.
Implementation of intelligent automation tools definitely has a positive effect on business development. The main benefits are:
- Better use of equipment and manpower
- Increased efficiency
- Lower costs
- Better customer services
- Improved security
- People can focus on most critical issues and apply more creativity due to elimination of mundane work
If you are going to automate some processes in your enterprise, make sure that there is a solid background for IA implementation. The main challenges that must first be addressed include:
- Establishing a robust governance
- Creating the appropriate IT environment and technological ecosystem
- Developing the strategy of implementation, choosing the right tool for the right job
- Restructuring the existing system and retraining employees
- Teaching the IA system necessary metrics and assigning tasks to it
- Managing risks
Automation plus artificial intelligence create a new type of workforce that drives digital transformation and broadens business opportunities. IA is still a newborn in the world of technologies, but it learns and develops fast, becoming an important player in the market. Intelligent automation trends are in the spotlight, capturing the attention of CEOs, developers and analysts around the world.
SaM Solutions can help your company automate various procedures and incorporate artificial intelligence, machine learning and other modern technologies into your projects. Our specialists have substantial experience in automation and creating various solutions with AI elements, for instance, Bing Speech API, Language Understanding Intelligent Service (LUIS), Face API, Computer vision API, a mobile application ViaOpta Hello and more. Contact our specialists and get answers to all of your questions.