The past six months have produced more digital transformations than the past decade. This is mainly due to the scaling of remote work, and businesses rapidly deploying the requisite technologies – particularly related to cybersecurity. With the influx of data from mobile devices, smart devices, and IoT-enabled products in our homes and businesses, the need to process and collect data while ensuring privacy and confidentiality will become even more critical – and complicated.
Meanwhile, the expansion of 5G networks will bring about a joining of the Internet of Things with AI to form “AIoT.” This explosion of data, while daunting, will be used in predicting behavioral transformation and help businesses understand how customers are adapting to a new reality.
AI had already seen rapid acceleration before the pandemic, as it allows for solving global and market problems faster, better, and at scale. According to GVR, the global AI market size was valued at $39.9 billion in 2019; between 2020 and 2027, it’s expected to grow at a compound annual growth rate (CAGR) of 42.2%.
Organizations will need to enable better access to information, to augment that information with better insights, and to have the ability to respond quickly to the implications of those insights. This will lead to smarter clouds, smarter data-management systems, and a push to automate any task that can be automated.
Consequently, 2021 will see companies relying even more on AI to automate and augment their core business processes. Wipro’s AI experts predict industrial organizations will increase their AI investments, thus creating a need to develop a disciplined AI-engineering process via a governance body. Wipro’s HOLMES™ ETHICA framework can act as a guiding principle to assist companies with model deployment and monitoring. As responsible AI emerges, we will see the operationalization of AI accountability.
With all of this development and evolution, we foresee nine digital and AI trends that will resonate across industries in 2021.
1) Smarter Data Management
Self-organizing data-management capabilities will emerge to ease data integration, cleansing, organization, storage, and access for transactional and analytic purposes. In the finance sector, Blockchain and AI will start to align more seriously to support data provenance, integrity, and usage. In fact, Wipro has already collaborated with a British bank to automate and improve their data quality-management process by using AI to capture, clean, and maintain accurate data.
2) Smarter Data Analytics and Insights
AI-powered tools can provide forecasts with high accuracy and enable real-time updates for data analysts. In 2021, many companies will introduce recurrent neural networks to obtain highly accurate forecasting information, and deep learning solutions will be embedded to get hidden patterns and actual forecasts. Such analytics will help detect possible cases of fraud, while AI can help marketers predict the next best action or the perfect offer. Already, Wipro has helped transform the S&OP process of a Saudi Arabian multinational chemical manufacturing company to glean valuable AI-driven insights for decision-making and automation.
According to Forbes, from January to April 2020, there was a 238% rise in attacks on banks, and a 600% increase in attacks on cloud servers. AI-supported systems will increasingly spot fake digital activities or transactions that follow criminal patterns. Video surveillance is just one area where on-device AI is enabling a fundamental shift, with new analysis technologies enabling greater insights as well as more personalization in healthcare, retail and aviation, among other sectors. In the coming years, face-recognition systems will become even more sensitive and precise.
4) The Joining of IoT with AI (AIoT)
The Internet of Things will continue to expand quickly: Transforma Insights forecasts that the global IoT market will grow to 24.1 billion devices in 2030, generating $1.5 trillion in revenue. AI will join with IoT to produce new technologies with the potential to offer real-time information in software and CRM programs, and myriad applications for smart buildings, smart cities, retail environments, and more.
5) Behavioral Transformation
This explosion of data will be used in part to predict behavioral transformation, helping business understand how their customers are adapting to a new reality. The collection and use of behavioral data – the Internet of Behavior (IoB) – will affect how organizations interact with people in order to change their behavior. Commercial vehicles can use telematics to monitor driving behaviors to improve driver performance, routing and safety, for example. Or, as Wipro saw recently with a British multinational insurance company, behavioral data can be leveraged to develop tailored pricing options.
AIOps enables “IT operations and other teams to improve key processes, tasks, and decision-making through improved analysis of the volumes and categories of data coming their way.” In 2021, we will see more AI solutions that can detect and remediate common IT problems on their own, perhaps proactively self-healing certain malfunctions to reduce system and application downtimes. One British multinational insurance company engaged Wipro to leverage Advanced natural-language processing (NLP) over machine- and human-generated logs to predict and remediate customer-facing incidents. This system will help reduce the volume of repeat incidents that previously required time-consuming and costly manual management.
The acceleration of digital business requires efficiency, speed, and democratization. Gartner predicts that we will see more intelligent automation initiatives to boost productivity, cut costs, improve accuracy, and enhance customer experiences. Robotic process automation (RPA), machine vision and NLP are key tools in this regard and will be applied to a variety of applications and processes.
8) Bringing Discipline through AI Engineering
According to Gartner, only about 53% of AI projects successfully make it from prototype to full production. As businesses struggle with maintainability, scalability, and governance, AI initiatives have historically failed to generate the hoped-for returns. In 2021, businesses and organizations will embrace more-robust AI engineering strategies that improve the performance, scalability, and reliability of AI models and deliver the full value of AI investments. Recently, Wipro helped a UK health organization establish an AI center of excellence to implement and deploy AI/ML projects at scale. This initiative resulted in best-in-class healthcare systems and standards, while improving the organization’s ROI and reducing costs.
9) Smarter Clouds
Companies will need to address the challenges of exponential data growth while also being proactive on issues like privacy, security, and compliance. Possible solutions include:
- Hybrid cloud data architectures: According to Forrester, the global public cloud infrastructure market will grow 35% percent in 2021, to $120 billion, with cloud system infrastructure services (IaaS) spending projected to increase 26.9%, to $65.3 billion. Yet the next few years will see hybrid cloud data architectures – which mix private cloud, public cloud and on-premises infrastructure – become dominant. Distributed computing technologies such as Kubernetes have made hybrid and distributed cloud infrastructures more manageable and operationally agile. Hybrid cloud implies a certain level of workload portability, orchestration, and management integration across these environments. It also gives businesses more data deployment options and greater flexibility by allowing the movement of workloads between public and private clouds as costs and computing needs change.
- Edge computing: Smartphones, smartwatches, and IoT-enabled devices transmit a vast amount of data. Processing and collecting this data is a complicated procedure that requires all information to be shared with cloud-computing devices. This becomes even more challenging if there is no internet connection. One solution is edge computing, which brings computation and data storage closer to the location where it’s needed, thus improving response times and saving bandwidth. This offers real-time data processing and is more efficient than cloud-computing services. It also costs less and saves time.
- Security: Data may travel between different distributed nodes connected via the internet, potentially requiring special encryption mechanisms independent of the cloud to ensure privacy and confidential computing. Companies will move to encrypting the entire computing process, not just the data, creating additional layers of security around sensitive information.
COVID-19 has accelerated digital transformations worldwide, pushing AI to combine with existing technologies such as data management, cybersecurity, analytics, IoT, automation, and IT operations. In each case, these technologies have been enhanced in terms of size, speed, productivity, and cost.
At the heart of this AI acceleration is an explosion of data, not just from office buildings and company computers, but from remote locations and billions of internet-enabled devices. 2021’s tech changes will revolve around collecting, aggregating, and managing this new and huge volume of data, using it in real-time to generate insights, and making accurate predictions that will help all industries make more-informed business decisions.