10 Artificial Trends to Watch in 2020

Many people and businesses are getting involved in artificial intelligence (AI), but how many are doing it well? Statistics indicate that the many benefits of AI have yet to be realized in many organizations.

Nine out of 10 companies may have made investments in AI, but 70% report they have seen little impact to date, according to a 2019 MIT report on artificial intelligence use in companies across the globe. (Enterpriseproject.com).

The report stated that CIOs need to be more effective in assessing the value of their AI assets and prove the ROI is worth the investment. Some experts, such as Kara Longo Korte, director of product management at TetraVX, says that 2020 will be the year when organizations focus more on the value AI brings to their business. They will get out of experimentation mode and accelerate AI adoption.

Some of the unfolding AI trends that wise IT leaders may want to follow include:

IT Leaders Will Focus on Measuring the Impact of AI Initiatives

Fewer than 20% of companies have reported business gains from AI in the last 36 months, according to the MIT study mentioned above. This must change in 2020 because of the large investments companies have made in AI.

A way to make this happen is to change how results with AI are measured. Perhaps focus on reporting about things such as ease of use, customer satisfaction and enhanced processes. Experts say CIOs will need to put more money into understanding how AI can help their companies and bring in solutions that offer solid ROI.

Operationalization Is Vital

AI can become the new operating system for the organization. Over the last 10 years, companies have been learning about AI and began working with it. But putting AI models into actual production has been difficult. 2020 could be a tipping point for designing and implementing the infrastructure needed to support AI deployments, offering integrated learning environments and data environments that support AI decision making.

Data Governance Will Become More Pronounced

2020 will feature AI coming into production, but it also will require IT departments to work with the chief data officer and her organization. The problem is sourcing data from many applications and convincing gatekeepers of data to play ball.

Organizations understand the need for the best quality data as the foundation for AI, so in 2020, there may be a better appreciation and need for solid data governance, data engineers, data analysts, and machine learning engineers.

The goal will be to devise a data pipeline that can handle continuous curation to create more successful AI projects. That is why chief data officers are more likely to utilize AI and deep learning for insights initiatives than companies without CDOs.

AI Professionals Will Stand Out

One of the top jobs in Linkedin’s Top 15 Emerging Jobs in the United States for 2020 is AI specialist. Hiring good artificial intelligence professionals has grown almost 75% annually over the last 48 months, Linkedin says. AI and machine learning are becoming synonymous with innovation. Data at Linkedin shows that it is more than just industry buzz. Hot markets for AI professionals are San Francisco, New York, Boston, and Los Angeles.

Data Modeling Will Become More Common

We should expect a shift from cloud-only to cloud-edge hybrid methods to allow machine learning (ML) in 2020. Being able to do high-fidelity, high-resolution, raw machine data analysis in the cloud is expensive and cannot happen in real-time because of ecosystem and transport considerations, according to Senthil Kumar, the VP of software engineering at FogHorn. As of today, companies often settle for small sample sizes or time-deferred data for their projects.

Forrester estimates that edge cloud services will grow by 50% in 2020. If edge-first solutions are implemented, organizations will be able to synthesize their data locally and deliver better predictive capabilities.

AI Will Be Important for B2B

B2B sales and services’ complexity will benefit even more from AI than consumers. Deep and machine learning make it possible for B2B users to match and define complex requirements to trading partners through an intuitive process and a good understanding of trading partner strengths and abilities, according to Keith Hausmann, chief revenue officer at Globality. User experience will get better as AI understands individual preferences better, as well as company requirements with every interaction.

Man and Machine Will Work Together at Contact Centers

Consumer desire to get better service on various digital channels challenges contact center teams. Team leaders need to deal with long wait times, difficult customer journeys, and overwhelmed telephone agents. AI can help agents, allowing them to provide better, more timely responses.

AI in call centers comes with its own challenges, however. It is vital that companies keep their customer service as human-oriented as possible to ensure that the customer journey does not look too automated.

Some brands are using chatbots to reduce customer service costs, but projects that are too ambitious may not resolve customer issues.

Automation Could Increase Significantly

Hyperautomation could be the word for 2020. This means the increased application of AI and ML to fully automate processes and help human beings do their jobs across many tools and at a level of better sophistication. In fact, Gartner has said hyperautomation will be a top strategic technology trend in 2020. (Gartner.com)

Heterogenous Architectures Will Appear

Applications and networks with AI today rely on a variety of different process architectures. This will probably change in 2020. The new generation of AI and ML architectures will feature multimodality and could require more computing resources for their operations. Some top chip manufacturers may move away from their proprietary software stacks and use open Software Development Kits.

Mistakes Will Be Made With AI

AI is far from perfect, and it can increase bias and discrimination. There could be some high-profile public relations disasters, which can damage some companies. Overall, though, trust in AI will not be damaged in the long term.

While AI can encourage discrimination, misuse of facial recognition and overuse of personalization can freak out some customers, these mistakes will highlight how important appropriate AI development and deployment are in the long term.