A decade is coming to an end. We’ve seen major breakthroughs in science and technology and we’re looking forward to new breakthroughs in the upcoming decade. Such times lead us only to wonder what the future holds. IDC and Forrester have issued their predictions for what we’ll be seeing in the AI sector these upcoming years.
AI in Automated Processing
Forrester predicts that in 2020, 25% of the Fortune 500 (the top 500 ranked largest US corporations) will add artificial intelligence building blocks to their RPA (Robotic Process Automation) efforts which will in turn help increase the use of AI in automated processing. Forrester says RPA requires “intelligence” and AI requires “automation to scale”.
IDC also predicts that by 2022, 75% of enterprises will use AI-based software in the automation of technology and process development which will help revolutionize the industry.
Incorporation of AI in Products and Services
By 2024, AI will be an integral part of business. An estimated 25% of the overall spend on AI solutions as “outcomes-as-a-service”. Artificial Intelligence will help redefine user experience by incorporating augmented reality, speech, natural language, computer vision and virtual reality. We’ll see AI incorporated in all types of products and devices over the several years.
Risks with AI Technology
As adoption of AI increases, so will the risks. Forrester warns that by 2020, 3 high-profile PR disasters will taint reputations as the possibility of AI malfunction will multiply. The spread of deepfakes, misuse of facial recognition, and over-personalization are some examples for starters.
IDC predicts that by 2021, 15% of customer experience applications will be hyper-personalized as newer RL Algorithms (Reinforcement Learning Algorithms) emerge. Forrester, however, is positive that none of these will slow down the adoption of AI. Instead, they will increase the demand of designing and testing AI systems capable of tackling these risks.
IDC predicts that by 2020, over 20% of the G2000 companies will have formal programs to monitor their digital trustworthiness as digital trust becomes a critical corporate asset. Companies will also start using AI, ML and deep learning for their insight initiatives.
According to the IDC “effective use of intelligent automation will require significant effort in data cleansing, integration, and management that IT will need to support. Resolving past data issues in legacy systems can be a substantial barrier to entry, particularly for larger enterprises.”
We don’t see any consistent adoption of AI for now. Companies either require AI or do not, forming a digital divide. Either that or they do not house the required highly-skilled engineers.
Changes in the Workforce
Forrester predicts that by 2002, the elite class of tech will increase the demand of AI plus design skills. The key will be pairing human centered design skills with AI development capabilities. Coming to the workforce, IDC predicts that by 2024 around 75% of enterprises will invest in the retraining and development of employees to adapt to the emerging needs of AI adoption.
The workforce will expand and IT organizations will manage and support a growing workforce of AI enabled bots in the automation industry. Conversational AI will also increase in demand however four out of every five conversational AI interactions will fail to pass the Turing Test (Designed by Alan Turing to test a machine’s ability to exhibit intelligent behavior). By the end of 2020, conversational AI will still power fewer than one in five successful customer service interactions.
As edge computing is on the rise, so will IT be challenged to manage and control edge processing devices. BY 2023, says IDC, nearly 20% of servers processing AI workloads will be deployed at the edge. By 2025, 50% of computer vision and speech recognition algorithms and modules will run on the edge.
By 2025 we’ll see artificial intelligence in nearly all new enterprise applications. However, truly game-changing AI embossed applications will only represent 10% of this total. The adoption of AI is already on the go, but mass revolution is still to come.