The AI market is expected to be worth more than $190 billion globally and to generate revenues of another $119 billion per year by 2025, in just three years.
Gestión
13 January 2022
During 2022, artificial intelligence (AI) and machine learning (ML) will be technologies that will continue to make marketing, both B2B and B2C, more efficient, more personalised and agile. That is why it is very important for professionals in these areas in companies to keep up to date with the latest trends, according to the iprofesional portal.
El mercado de la IA prevé alcanzar a nivel mundial un valor de más de 190 mil millones de dólares y generará ingresos por otros 119 mil millones al año en 2025, es decir, en apenas tres años.
The AI market is expected to be worth more than $190 billion globally and to generate revenues of another $119 billion per year by 2025, in just three years.
In the short term, 75% of companies will move from pilot testing to implementing their artificial intelligence projects, increasing their analytics and streaming data infrastructure by a factor of five. The acceleration in process automation will be a never-before-seen event.
According to global surveys, more than half of B2B marketers see AI as a valuable tool for their sales and branding strategies. Those who have already implemented projects have achieved significant financial benefits and improved their ability to innovate, as well as helping to personalise experiences for their customers.
But beyond what it has enabled so far, challenges remain. Many company CEOs believe that AI and automation will increase vulnerability and disruption in the way they do business, and that by 2022 there will be many erroneous outcomes due to inaccurate processing of the data that has been collected, among other things.
Faced with this scenario and the need or decision to incorporate AI or ML into business strategies, it is important to bear in mind the following five points that will be trending in 2022:
1. ROI-driven Artificial Intelligence Implementation
Some of the common reasons for unclear financial outcomes of AI projects include limited access to quality data, lack of resources and skills to implement artificial intelligence at scale; or there is a tendency to overcomplicate things or fail to get buy-in from the executive level.
That's why one of the biggest trends in AI this year, and beyond, will be to take an incremental, ROI-driven approach to AI development. Defining clear objectives at the start of a project is key to improving the project's success rate.
The acceleration of process automation will be a never-before-seen event.
2. Hyper-automation by Artificial Intelligence
In a pandemic-stricken world, the role of information technology has shifted from supporting business operations to delivering business value. This shift has had a profound impact on AI innovations and trends.
Driven by 5G deployments, more powerful computing chips, falling sensor prices and flexible cloud services, the convergence of robotic process automation (RPA), artificial intelligence and Internet of Things (IoT) technologies has become a viable reality. Recent advances in artificial intelligence will help businesses achieve resilience and significant cost reductions.
3. Responsible Artificial Intelligence
Both government entities and private companies should focus on creating intelligent systems that explain the rationale for their decisions and do not discriminate against people on the basis of ethnicity, age, gender, religion or place of residence.
In addition, stakeholders must clearly communicate the benefits of automation to bring employees on board and encourage them to participate in AI implementation and training. There is a branch of AI specialists who focus on generating "Explainable AI" that contrasts with the current black box of Neural Networks.
4. Artificial Intelligence as the leader of the cybersecurity revolution
The use of intelligent algorithms for the prevention of cyber attacks has become one of the most important artificial intelligence innovations in recent years. Forward-thinking companies leverage it to detect suspicious traffic within corporate IT networks, identify malicious software, detect infected links in employee emails and even to model cyber-attack scenarios based on vulnerability assessments.
Companies looking to implement AI innovations must closely monitor all data presented to artificial intelligence models, review the real-world data used for model training, and build the elements of randomness into their artificial intelligence models.
Cristian Santander: "Defining clear objectives at the beginning of a project is key to improve the success rate of the project".
5. Artificial Intelligence as a driver of corporate sustainability
While green artificial intelligence innovations are still rare, several implementations have proven to help companies achieve their sustainability goals.
AI is set to become increasingly intelligent (redundant), creative and honest in the coming years. According to analysts at Forrester, new AI business models will be able to optimise the convergence of the digital world with the physical world and drive the 'anything-as-a-digital-service' trend. The impact on the customer experience is going to be huge.