Organizations — ranging from startups in the technology industry to multinational corporate behemoths — are constantly looking to adopt cutting-edge technologies for their business growth. Artificial intelligence (AI) is one example of such a technology that has the potential to offer a variety of innovative business solutions.
According to IDC research, governments and companies will spend more than $500 billion on AI technology globally by the end of 2023. What impact will it have, and how will it be used?
This article will delve into the five most important trends shaping the world of Artificial Intelligence in 2023. We’ll also provide a brief overview of each trend, its significance, and examples of its application.
Digital Twinning
Digital twins are virtual replicas of physical systems — assets, devices, or processes — that allow businesses to perform analysis, run simulations, and monitor physical systems. As a result, fewer physical prototypes are required, the design process moves more quickly, and the quality of the finished product or process is improved.
So, where does AI come into play? Artificial intelligence can increase the effectiveness of digital twinning by offering insights that go beyond what real-world sensors can detect. AI can independently decide which tests to run and then predict which actions would result in the desired outcomes based on the data it receives.
Additionally, algorithms are quick to detect any unusual data from the sensors. Below is a list of possible digital twining AI advantages across use cases.
- Enhance supply chain agility and resilience.
- Reduce product time to market.
- Enable new business models (i.e., product as a service)
- Improve product quality
- Drive operational efficiency
- Improve productivity.
Digital twins have many applications in healthcare, where data accuracy is paramount, and mere seconds can impact the long-term quality of a patient’s life. For example, digital twin-assisted Remote Patient Monitoring (RPM) dramatically improves access to timely care and diagnostics.
Challenges of digital twinning
Significant challenges to the growth of the Digital Twin market include the high cost of deployment, increased demand for power and storage, integration challenges with existing systems or proprietary software, and the complexity of its architecture.
It is paramount to consider these potential challenges and work on probable methods for resolving these limitations moving forward, especially as more manufacturers will use digital twin technology to improve procedures and generate real-time database judgments in the coming years.
Augmented Intelligence
Artificial intelligence (AI) is utilized in “augmented intelligence,” which focuses on how AI can help improve and augment human reasoning and intelligence. The term refers to the collaboration of humans and artificial intelligence to improve, rather than replace, how people work.
Augmented intelligence can enhance human decision-making, save time by sorting through high volumes of data, drive business and sales by successfully predicting patterns, remove human error and bias in data interpretation, and allow humans to make more accurate data-driven decisions in real-time.
For instance, it can be applied to online shopping to increase traffic based on customer preference predictions. Using augmented intelligence technology, the biotech company Freenome analyzes biological data sets to sift through blood tests in search of early cancer warning signs. Examples of augmented intelligence include Siri, Alexa, and Google Home, among other virtual assistants.
Gartner estimates that adding AI has already increased worker productivity by 6.2 billion hours and generated $2.9 trillion in business value worldwide. Additionally, many other AI projects will be eclipsed by decision support/ augmentation by 2030.
Challenges of augmented intelligence
One negative challenge that augmented intelligence faces is discrimination and bias in design and implementation. AI algorithms learn from the data they are trained on, and if the data contains biases, the algorithms may reinforce those biases. The consequences of this might be discriminatory, harming marginalized groups, or escalating pre-existing prejudices.
While AI has the potential to improve productivity and streamline processes, it may also result in job displacement in specific industries. Re-skilling and up-skilling initiatives must be put in place to address this challenge, ensuring a smooth transition for workers and equipping them with the skills they need to succeed in the changing job market.
The AI trends discussed in this article are just a glimpse of what lies ahead. From digital twining/ computer vision and augmented intelligence, we are witnessing the remarkable advancements that are being made in AI systems.
However, our journey is far from over. In the next part, we will turn our attention to three other fascinating aspects of artificial intelligence.
