The increasing connectivity of businesses and technology has accelerated the pace of change. What we are witnessing today is a state of rapid and steadfast digital transformation that thrives on innovation and influence fueled by emerging technologies such as Artificial Intelligence (AI) and predictive analysis. In fact, the adoption of AI in the enterprise is shaping the way businesses operate from cost savings to creating new markets, products, and services. To remain competitive, and ahead of the curve, investing in the new generation of ideas is essential. This serves as a catalyst for profound, positive change for businesses and catapults them to embrace the much-needed disruption that is shaping the future of enterprise technology.
The Challenge of Market Size
As per IDC - by 2026, 40% of total revenue for top Asia-based 2000 organisations will be generated by digital products, services, and experiences while IDC's Worldwide Semiannual Artificial Intelligence Tracker (1H22), states that the worldwide AI market, including software, hardware, and services, is forecast to grow 19.6% YoY in 2022 to $432.8 billion and is expected to break the $500 billion mark in 2023. Meanwhile, the predictive analytics market in Asia Pacific is expected to grow from US$ 2,893.78 million in 2022 to US$ 9,597.20 million by 2028 with a CAGR growth of 22.1% from 2022 to 2028 with CAGR growth of 22.1% from 2022 to 2028 (Research and Markets).
While the pandemic speeded the adoption of emerging technologies, AI is becoming a must-have for most organisations, and the upward trajectory of the AI market is forecast to continue year-over-year. So, why are organisations betting on AI? While the obvious answers lie in fostering innovation, optimising business efficiency, and improving productivity, a significant aspect is the way it combines with other technologies to create efficiencies.
To maximise the advantages in the long run, business and technology leaders need to address the critical challenges it brings, especially in the realm of talent and data. You need the right skill sets to make AI work. Lacking the right level of experience and training can hinder progress. Often businesses are simply underqualified to lead an AI implementation, resulting in inefficient processes, integration issues, or ongoing manual work that undermines the solution’s value. AI and data are synonymous as data quality and availability are necessities for building AI capabilities. So, the better the data, the better the outcomes.
AI & Predictive Analytics in action
Ease of deployment and building a scalable architecture via secure and simplified cloud-native technologies helps in addressing a complex AI environment across all verticals. To cite an example in the supply chain industry, where the speed of innovation leads to unprecedented dynamics, traditional AI can be difficult to adapt to support the agility and velocity required. Real Time Instant Machine Learning can be used to complement what-if and simulation scenarios for budget exercises, adapt maintenance for product support strategies, run forecasting, and conduct risk assessments among others. This helps in shortening the time to run and compare scenarios and easily interface with simulation tools.
To cite another example in the contact centre industry, where having a forecast for just one perspective or one or two prediction horizons is not sufficient, having the capability to build models and make new predictions instantly is necessary for the successful management of resources.
The Opportunity for Integrated Transformation
Undoubtedly, AI is transforming the way businesses interact with their customers and partners and enabling new business models. However, it is beneficial to take an integrated approach to business transformation driven by AI. With the rise in high-growth technologies, an average customer often employs more than 50 vendors in their IT stack and if they are adopted in silos, without an enhanced level of connectivity – then it impacts performance and business outcomes. The adoption of AI and Predictive Analytics must integrate the strengths across the board, which can help to scale the business at speed.
In this context – leveraging the services of a Centre of Excellence - that carries an end-to-end solution stack of hyper-converged infrastructure, next-gen solutions, hybrid cloud, and DevOps helps to integrate data analytics and artificial intelligence solutions seamlessly providing a robust value proposition to business strategies.
AI and data are changing the relationship between humans and machines. Leaders across industries are banking on the connection between human and artificial intelligence. AI could process, analyse and evaluate the vast amounts of data generated today, allowing humans to focus on creative high-level thinking. What does this mean for channels and partners? It means the opportunity to bring an end-to-end predictive analytics solution and AI approach to solving business problems and leverage the power of integrated business transformation to improve operational efficiency and facilitate innovation across all sectors.