AI is hot. Every enterprise worth its stock price is looking out for ways to harness its power to not only stay relevant but also gain a competitive edge. That’s why it’s not surprising that over 37% of businesses have adopted or are planning to adopt BPM systems in their processes.
AI-driven technologies are changing the way organizations conduct business. Once centered on the priority of cost-cutting and process efficiency, modern BPM systems are more focused on providing the ultimate customer experience.
For example, instead of sticking to reactive analytics, AI’s cognitive systems offer proactive and predictive analytics. That way, it not only helps improve performance efficiency and effectiveness but also insights that managers can use for decision-making.
BPM and AI deliver escalating efficiency
Today, thanks to advancement in technology, business process-based applications are getting more sophisticated. While the new development might be good news, the pronounced effect of blocked processes or delays still haunts most businesses.
But, the recent developments in AI are making it possible for businesses to predict future prospects and plan ahead. Besides, it has become easier to align future constraints with resources, as a result avoiding bottlenecks in the future.
AI intersections in BPM systems
A research by Forrester points out Text analytics/Natural Language Process (a type of AI) as “one of the primary intersection points between artificial intelligence (AI) and business process management (BPM).”
Besides, the other intersection of AI that affects BPM revolves around machine learning. Machine learning gives AI engines ability to assess the efficiencies of the automated processes in your businesses and where possible offer recommendations. Based on these recommendations, businesses can modify business process, logic and as a result, escalating process efficiency.
The truth is, the idea of using analytics to monitor process execution is nothing new. But, and artificial intelligence takes it a notch higher. By using machine learning, AI can easily provide guidance on process tuning and optimization.
Thanks to streamlined backend operations, state-of-the-art user interfaces, smother processes AI-based BPMs helps improve process efficiency, improve the rate at which businesses react to the markets. Besides, these factors also lead to increased adaptability to changing business environments.
How is AI impacting the business processes of today?
Using AI-based BPM systems facilitates better process-flow pattern detection and business metrics predictions. It also helps provide corrective actions. Here are some of the ways in which AI is revolutionizing how business management their operations:
Machine learning – from data to prediction
Thanks to advancement in AI, so many sophisticated machine learning algorithms are coming up. For example, today, algorithms such as decision trees and neural networks are much more available in ready-to-use libraries.
These algorithms will help business owners, managers and/or the employees have ease of solving difficulties that they encounter when describing properties for input data that determine the expected output. For example, using search algorithm and hybrid deep learning, researchers were able to master the game of Go, one of the most complicated with more positions than the number of atoms in the universe!
On the same note, machine learning-based BPMs can easily detect patterns that are not easily noticed by human managers. The ability to detect these patterns successfully can be employed in BPM to spot deviating behavior - for example credit-card frauds – or segment data for particular services, like segmenting prospects for marketing purposes.
That is not the only way machine learning methods are helping fuel this change bandwagon. These methods also offer the flexibility you need to apply when changing inputs. As a result, increasing the flexibility of business processes – and possibly adjust the assessment in case of changes in the circumstances.
From prediction to decision
Thanks to advancement AI, it has become easier to apply decision theory and evaluate uncertain and conﬂicting situations. AI makes it easier both when you are working with a given set of preferences and within in a ﬁnite or inﬁnite decision horizons.
As a result, AI-based decision-theoretic models are responsible for decisions that are taken within a business process. For example, you can use such models to decide whether you want to give a recommendation to a customer or buy or sell products, stocks, etc.
For example, think about the complexities you encounter when making each marketing decisions.
You need to map out the ever-changing customer needs and align their services or products to these needs. Besides, your knowledge of the evolving customer behavior is a crucial tool you need to come up when coming up with both short and long-term marketing strategy.
AI-based BPM provides you with modeling and simulation techniques that offer you reliable insight into consumer behavior (in real-time) and predict future consumption trends.
Search algorithms – from decision to action
The increased power of AI has enabled many BPM vendors to develop different search algorithms that have been incorporated into powerful problem-solving and optimization techniques.
Based on these techniques, vendors may come up with a discrete model defined by a set of states and actions.
Using the defined state and action, businesses can easily define the search space. In this case, states become the nodes of the underlying graph, and the actions are the possible transitions between the edges of the state of your graph, which are marked by the edges of the graph.
Advancement in AI has to lead to the birth of state-based search algorithms. The models can be applied in many powerful discrete modeling techniques to optimally solve scheduling, planning and a slew of other related problems encountered in business process management.
Summing it up
AI-embedded BPM solutions are offering businesses an opportunity to differentiate themselves from the competition. As a result, enterprises can transcend the usual performance blockades so that they can achieve high levels of efficiency and quality.
Today, AI is no longer perceived as the end but only a means towards effectiveness and efficiency. Various businesses – both small and large – are slowly realizing the importance of adopting AI-based BPM software to achieve optimization and ﬂexibility of business processes.