Ensuring digital effectiveness requires insights into how enterprises can provide the best outcomes through people, processes and technologies. Armed with those insights, business and technology investments can effectively innovate and streamline organizational processes.
Global enterprises are building new digital platforms to replicate human actions and eliminate routine tasks to achieve greater outcomes. Automation creates a new paradigm of people, processes, information and technology collaboration, resulting in improved effectiveness through increased investment in intelligent automation software. Given these positive trends, the ISG Provider Lens for Intelligent Automation forecasts that the intelligent automation market will exceed $19 billion in 2023.
Intelligent automation is marked by the convergence of advanced technologies such as machine learning, robotic process automation and natural language processing. This fusion is leading to the emergence of sophisticated systems capable of performing complex tasks with minimal human intervention. Examples include:
- Explainable AI: Explainability is a critical factor in gaining trust and understanding how AI-driven decisions are made. In 2024, explainable AI (sometimes abbreviated as XAI) will be a key technology trend in intelligent automation. Enterprises increasingly demand transparency in automation systems, especially in industries where decisions impact individuals’ lives or have significant financial implications. XAI technologies will enable users to understand, interpret and trust the outputs of complex machine learning models, making automation more accessible and accountable.
- Advancements in conversational AI: NLP already plays a significant role in conversational interfaces and chatbots, but in 2024, advancements in NLP will take intelligent automation to new heights. Enterprises will integrate more sophisticated conversational AI systems that comprehend and respond to human language in a more nuanced and context-aware manner. This trend will drive improved customer support, workforce interactions and overall communication processes within enterprise organizations.
- Edge computing for intelligent automation: In 2024, there will be a shift toward processing data closer to the source, reducing latency and enabling real-time decision-making. This is particularly crucial for automation applications that require quick responses, such as autonomous systems, smart manufacturing and IoT-enabled processes. Edge computing will enhance the efficiency of intelligent automation and address concerns related to data privacy and security by minimizing the need for transmitting sensitive information to centralized cloud servers.
Automation also improves customer experiences by providing immediate responses. Our Analytics and Data Benchmark Research found nearly one-half of enterprises consider robotic process automation important.
Enterprises are primarily guided by three objectives to undertake automation change:
- Address tight labor markets: There is a lack of skilled workforce to conduct digital transformation projects, making automation integral to modernization efforts. Automation enables business growth at a scale that surpasses human capability.
- Overcome technological debt: Legacy systems and processes hold back growth and innovation. IT investments are growing – namely those earmarked for artificial intelligence and not transformational programs. Larger digitization projects are likely to return to the discussion in the future.
- Plan for future computing structures: Technology architectures are increasingly decentralized. Enterprises must consider how the workforce has become remote or hybrid as well as the next-generation cloud decisions of hybrid and multi-cloud. The challenge of managing data, servers, access, endpoints, etc., is already happening.
Efficiency is also a key target for any enterprise organization, and automating business processes helps reduce the errors and inefficiency of manual work. Our research further finds that more than 44% of enterprises plan to change the technology assessment and selection process to improve operational efficiency and reduce costs. Of those planning to change, 1 in 5 are motivated to reduce errors and mistakes impacting the business.
The benefits of intelligent automation are driving new approaches to everyday challenges. We expect greater adoption of these business trends in 2024:
- Cognitive customization of customer experiences: As intelligent automation continues to evolve, businesses are increasingly maximizing analytics, ML and NLP to deliver highly personalized customer experiences. In 2024, the trend will move toward cognitive customization, where automation technologies analyze vast amounts of customer data in real time, enabling enterprises to adjust product and service interactions to suit an individual’s preferences and cognitive style. This will not only enhance customer satisfaction but also contribute to increased customer loyalty and improved brand perception.
- Ecosystem collaboration and integration: The scope of intelligent automation is expanding beyond individual business processes. In 2024, we expect a growing trend of collaboration and integration within business ecosystems. Enterprises will seek to create seamless, end-to-end processes by integrating intelligent automation across various departments, partners and the supply chain. This trend fosters a more connected and agile business environment, allowing enterprises to optimize operations, reduce friction in processes and respond rapidly to market changes.
- Ethical and responsible automation: With increasing reliance on automation technologies, ethical considerations are becoming a crucial aspect of intelligent automation strategies. Ethical automation is not just a compliance requirement but a strategic imperative for enterprises looking to maintain a positive reputation and navigate the AI governance landscape. In 2024, enterprise organizations will establish processes and governance for responsible and ethical use of automation to build trust with customers, the workforce and other stakeholders. This includes implementing transparent algorithms, addressing bias in machine learning models and adhering to regulatory frameworks.
These advancements are pushing the boundaries of what’s possible with intelligent automation, paving the way for a future where machines can learn, adapt and act in increasingly intelligent ways that benefit enterprises. Implementation of intelligent automation streamlines operations, reduces costs and enhances customer experiences. It is becoming a critical component of business transformation and modernization, driving unprecedented efficiency and productivity.
Regards,
Jeff Orr