2024: Automation Shaped By LLMs, Regulators, & Enterprise App Vendors

Once harnessed, AI represents a profound business transformation superpower, unlocking the potential of business models, cost structures and customer service and engagement. • Employees expect their enterprise systems to be as engaging, exciting and intuitive as consumer devices. Technology research company Gartner calls this a shift from technology-literate people to people-literate technology. • The digital workplace merges work and life—a virtual space with applications, services and information on demand.

That’s because the conversation around intelligent solutions, advanced automation and digital technologies like artificial intelligence (AI) and machine learning (ML) has veered off course for far too long. Cognitive supply chains are about more than just automation — they involve AI agents that can see, understand, decide and even act. These systems leverage unified data clouds that represent the entire supply chain ecosystem, allowing businesses to simulate and optimize scenarios in real-time, according to Usie. Cognitive automation can handle tasks that involve perception, judgment and decision-making, which were previously considered too difficult for automation.

The enterprise impact: Challenges and opportunities in AI automation

The goals of automation include improvements not only in productivity but also in quality and consistency. You’re automated on the low-end, but creating a category for high-end skill set employees to address and solve problems they previously didn’t have the time to work on. And the cost saving opportunity that cognitive-powered RPA introduces can be enormous — in some cases cutting up to 75 percent. By not having to constantly retrain an entire workforce or hire more people, a company frees up assets. Could the economic benefit that comes from AI be invested in efforts to support those who are impacted? With AI, companies and countries could follow a similar model as Norway did with its oil revenue, where the wealth generated is invested through the Government Pension Fund Global.

Deep tech disruption: How advanced technologies are transforming businesses

The company’s presentation of its 4NE1 robot in Munich was affected by traffic delays, showing both the challenges of logistics at trade shows and of meeting expectations for humanoid capabilities. Hence, the ability to swiftly extract, categorize and analyze data from a voluminous dataset with the same or even a smaller team is a game-changer for many. Small-sized companies with budget constraints can consider alternatives like including collaborative document-sharing tools with cloud access, which fosters teamwork and can be cost-effective.

• According to a McKinsey report, adopting AI technology has continued to be critical for high performance and can contribute to higher growth for the company.
• For Brunskill, the big question is how AI can integrate with humans to drive societal value, rather than acting like a thief of human creativity and ingenuity.
• McKinsey identifies early adopters as digitally mature larger businesses that will use AI in core activities through multiple technologies, and that focus on growth over savings.
• “While they are effective for predefined workflows, these methods lacked the flexibility and adaptability required for dynamic, real-world applications,” the paper states regarding earlier automation approaches.

Real-World Examples of Automation at Work

Higher-skilled job categories in medicine, legal services, accounting, finance and law enforcement are all in scope to be augmented and even replaced by cognitive technologies. In fact, while the transformational powers of robotics and cognitive automation are only in their infancy stage, the work of more than 100 million knowledge workers across the globe may be impacted by automation over the next 10 years. Cognitive automation — basically, the intersection of artificial intelligence (AI) and cognitive computing — has become one of the fastest-moving technologies because of the rise of the digital and connected workforce. According to one forecast, the global cognitive robotic process automation market will generate revenue of $50 million in 2017 and will expand at a compound annual growth rate of 60.9 percent from 2017 to 2026. Conversations at the highest levels of business have changed from efficiency-focused to intelligence-focused. Technologies are coming online that enable cognitive automation by modeling the intelligence of humans, extending their decision making models and refining them.

Vision System Reduces Image Processing Latency

This represents a potential $68.9 billion market opportunity by 2028, according to analysts at BCC Research, as enterprises look to automate repetitive tasks and make their software more accessible to non-technical users. The market is projected to grow from $8.3 billion in 2022 to this figure, at a compound annual growth rate (CAGR) of 43.9% during the forecast period. The technology essentially gives AI systems the ability to see and manipulate computer interfaces just like humans do — clicking buttons, filling out forms, and navigating between applications. Rather than requiring users to learn complex software commands, these “GUI agents” can interpret natural language requests and automatically execute the necessary actions.

A message from John Furrier, co-founder of SiliconANGLE:

On its website, Neura Robotics promotes its Neuraverse web platform approach designed to facilitate networking, collaboration and co-creation within its partner community. Changing the way we work—with the help of AI—necessitates changing our mindsets, starting at the top. In doing so, we can begin to seize the opportunities of AI as a solution to drive business transformation, economic growth and global prosperity.

• The workplace of the future will be designed to ensure ubiquitous, personalized and secure access to emerging new cognitive and analytic capabilities.
• Watson can take information about a specific patient and match it to a huge knowledge base of medical journals and documented treatments and outcomes for similar patients.
• In its simplest form, automation includes any improvement to a process that reduces human labor while resulting in an outcome that’s the same or better than that of the previous process.
• For example, millions of hours of driver decision making had to be modeled to make self-driving cars feasible.
• Imagine that assistant can also then learn over time, through real-life interactions with you and others in your profession, expanding knowledge and offering more precise assistance.

Developing this capability should and must progress much like the brain develops executive function (i.e., a learning period is needed when decisions are new, complex and when risks are high). According to a market report by Lucintel, the future of the global cognitive robotic process automation market looks promising with opportunities in the finance and banking, telecom and it services, and insurance and healthcare markets. The global cognitive robotic process automation market is expected to reach an estimated $11.3 billion by 2030 from $5.9 billion in 2024, at a CAGR of 11.4% from 2024 to 2030. The major drivers for this market are increasing demand for automation across industries, rapid digitalization, and continual growth in e-commerce sector. The global supply chain is undergoing a fundamental shift, driven by the urgent need for resilience and responsiveness.