The sheer pace of technological change with respect to AI is putting pressure on teams leading to disagreements, mainly because business has unreasonable expectations on the speed and agility of new technology implementation. 88% of IT professionals claim they are unable to support the deluge of AI-related requests they receive at their organisation. Executives from UiPath, Salesforce, ServiceNow, ManageEngine, share their perspectives.
Leading enterprises use an AI-powered automation platform that understands, automates, and operates end-to-end processes. Automation platforms work alongside existing enterprise technologies using AI to propel people forward by removing friction, waste, and effort to allow them to achieve business outcomes faster, more accurately, and more efficiently.
Some of the key tools and solutions leading the innovation this year include Intelligent Document Processing, Communications Mining, Process and Task Mining, and Automated Testing.
“Automation is the best path to deliver on whatever AI conceives, seamlessly integrating intelligence into everyday operations, automating all backend processes, upleveling employees, and revolutionising entire industries,” says Mark Gibbs, EMEA President, UiPath.
According to Jessica Constantinidis, Innovation Officer EMEA at ServiceNow, Intelligent Automation is a combination of Robotic Process Automation, Artificial Intelligence and Machine Learning, combined with well-defined processes, to determine automated outcomes in decision making.
“Hyperautomation is a business-driven, very strict and well thought through approach that enterprises can use to make business decisions, based upon quick feedback of process and data analysis inside the organisation,” adds Constantinidis.
“Companies want to embrace technology and leverage their data, but the pace of change often leads to confusion and an inability to act, stifling innovation and agility. Organisations can raise their productivity, improve visibility, and transform their operations by deploying AI and Hyperintelligent Automation tools and solutions,” says Thierry Nicault, AVP and General Manager, Salesforce Middle East.
By embracing the power of AI, enterprises can seize opportunities for growth and contribute to the region’s economic diversification. Automation is making lives easier, and combined with technology, it has improved business revenues and spurred innovations.
“Hyperintelligent Automation powered by AI takes automation to the next level. It utilises tools such as Natural Language Processing, and Intelligent Document Processing, to detect anomalies, forecast business trends, and empower people to make better-informed decisions,” says Ramprakash Ramamoorthy, Director of AI Research, ManageEngine.
Robotic Process Automation, and Business Process Automation, automate existing workflows. These innovations are further democratised by low-code and no-code applications that empower anyone to build intelligent workflows, while AI models can become subject matter experts when trained with domain-specific data.
Push backs from IT
“Challenges typically vary between different organisations. A common one is the sheer pace of technological change, particularly with respect to AI, which can put pressure on teams, leading to disagreements,” says Salesforce’s Nicault.
This is borne out by research. A recent Salesforce survey of 600 IT professionals revealed a new mandate from their leaders: incorporate Generative AI into the technology stack rapidly. However, IT is pushing back, raising concerns over resources, data security, and data quality.
Nearly three in five IT professionals said business stakeholders hold unreasonable expectations on the speed and agility of new technology implementation. In fact, 88% of IT professionals claimed they were unable to support the deluge of AI-related requests they receive at their organisation.
Most organisations do not have any idea on the full extent of the processes in their organisation, mainly due to lack of transparency across business units.
“As automation needs full intelligence on all business units, and potential scenarios coming out of results, lots of companies only see snippets of the process. Therefore, identifying what you really want, and how that results into automated processes, is a challenge for most organisations,” says ServiceNow’s Constantinidis.
Other issues include data validation, data classification and data privacy, and these need to be priorities before full Hyperautomation is possible, since AI system will take the data as true values, without verification.
“You would need AI skills to teach and feed the data, and you would need a data specialist to clean up your data lake. One important thing is governance and risk in classification of the data. So someone would need the skills to understand what data is allowed in AI and what is not. And you would also need the business insight into every business unit,” continues ServiceNow’s Constantinidis.
“Scenarios will need to be thought through to fill in the hyperautomated processes. How you run your business, using the new technologies and potential options for execution, will need to be re-evaluated, as that might be different to previous technologies,” adds Constantinidis.
“Automation cannot happen in a vacuum; it must reflect and be informed by the business users who know the processes and systems and will ultimately be the users and beneficiaries of the automation,” points out UiPath’s Gibbs.
Once an automated process is deployed, the work does not stop. Implementing a feedback and learning loop with human validation ensures a continuous cycle of improvement wherein new insights are used to refine the automation process, enhance model accuracy, and drive even bigger business impact.
“There can be challenges when adopting Hyperintelligent Automation tools and solutions alongside an enterprise’s existing workflows. While a willingness to adopt a newer technology stack is important, so is weighing the pros and cons of investing in these technologies,” says ManageEngine’s Ramamoorthy.
Enterprises should not join the AI bandwagon without proper planning and analysis of the needs of the company.
They can adopt Hyperintelligent Automation tools in smaller areas, such as using AI in chatbots for lead generation and customer support, marketing, and inventory management. AI is highly customisable, and it can be adapted to every enterprise’s specific requirements.
“One of the most significant challenges while adopting Hyperintelligent Automation is the complexity of shifting from legacy systems. In doing so it is also important to bridge the skills gap to ensure that specialised skills such as AI, ML, data science are in place,” says Bassel Khachfeh, Digital Solutions Manager, Omnix.
Alongside this, planning adequate budgets is also important as the process means heavy initial investments in technology, infrastructure and training. In reality, we all know that this can involve high financial costs.
Some of the other challenges include data quality and availability as well as accessing and managing data. Automation also brings in the cyber security angle and requires strong security measures that help in protecting sensitive data and systems.
Integrating business and IT
“The adoption and success of Hyperintelligent Automation tools requires a blend of IT and business skills,” says UiPath’s Gibbs. “These skills ensure organisations can effectively implement, manage, and optimise hyperintelligent technologies, aligning them with organisational goals and improving efficiency. Moreover, they help in maintaining compliance, fostering innovation, and gaining a competitive advantage.”
Key IT skills include expertise in AI, ML, data management, software development, cybersecurity, automation tools, and cloud computing. Business skills encompass strategic planning, change management, project management, process analysis, financial acumen, customer experience management, regulatory compliance, and leadership.
By combining these competencies, organisations can successfully navigate the complexities of AI and automation and drive sustainable growth and transformation.
“Enterprises need the right blend of IT and business skills. On the business side, there needs to be a deep understanding of processes, problem-solving, and change management. Together, they can identify automation opportunities, design solutions, and ensure the technology delivers value,” says Salesforce’s Nicault.
But success is not just about technological innovation. It is also about empowering humans to drive AI and use it in ways that are trustworthy and effective.
“We can lean into AI’s capabilities and free up people to do what they do best: be creative, exercise judgment, and connect more deeply with one another. This will create more productive businesses, empowered employees, and more trustworthy AI,” adds Nicault.
For better adoption of Hyperintelligent Automation tools, enterprises must address any lack of digital maturity and siloed data across departments.
“The business skills required are process analysis to identify the key areas where automation is required; change management skills to navigate the transition and ensure user adoption throughout the organisation; and finally, understanding and implementing data governance policies,” summarizes ManageEngine’s Ramamoorthy.
“From a business point of view, understanding the areas that are most likely to be automated and assessing the optimisation opportunities of workflows is key to the automation process. This has to have a good fit with the overall business goals,” says Omnix’s Khachfeh.
In doing so, one has to ensure that the process is aligned to follow regulatory, and compliance needs which are crucial to industry specific business needs. Technology is advancing at a fast pace, and entering this domain needs to be supported with a continuous application of innovations to identify opportunities for future success.
Transforming experiences and operations
“In the beginning we would have fully manual processes where data was analysed by people, then people would make a gut business decision and implement manually. With automation, that insight became a bit easier and the process was still fairly straight forward. If this, then that, and then we would let the person deal with it,” explains ServiceNow’s Constantinidis.
Hyperintelligence means you can now use the implications of results, plan for potential outcomes and avert crises, providing that you can imagine the scenarios at first, trust AI’s data accuracy and trust AI biased programming to make the right decision.
“The longer the system learns, the more accurate the result will be. But in this day and age, trying and failing fast is critical, so with Intelligent Hyperautomation you can easily learn the consequences of certain process decisions and their outcomes,” adds Constantinidis.
The ability to automate backend processes frees people from mundane, time-consuming aspects of their jobs so that their time can be spent on higher value work.
“Enterprises benefit from faster transformation of manual or paper-based processes and can access untapped automation opportunities and process enhancements,” says UiPath’s Gibbs.
This revolutionises customer experience and enhances business decision making at every level of the organisation, leading to greater innovation. Automation and AI helps enterprises in critical areas like supply chain management, regulatory compliance, and customer-facing processes.
“In the enterprise sector, Natural Language Processing can be used in chatbots to answer queries and retain engagement. It is also used to analyse and summarise documents, analyse sentiments, and derive insights from meeting transcripts,” says ManageEngine’s Ramamoorthy.
Intelligent Document Processing tools are specifically designed to automate documents such as invoices and contracts. Here the application of NLP and computer vision helps to make an impact on manual efforts by automating the process and streamline document workflows.
“Going a step further, Cognitive Automation platforms take Robotic Processing Automation a notch higher by integrating AI driven cognitive capabilities such as Natural Language Processing, Optical Character Recognition, and sentiment analysis. This is especially true in situations where more human understanding and decision making is required,” adds Omnix’s Khachfeh.
AI-powered chatbots and conversational AI assistants are extremely handy in the areas of customer interactions. What is more important is the personalised responses provided and the provision of handling complex queries without human involvement.
Hyperintelligent Automation solutions can also forecast future trends, analysing large volumes of enterprise data to give proactive measures for the enterprise.
