Artificial intelligence (AI)-driven automation has been acquiring a relevant role for companies in recent years, as it enables work teams to perform their functions more effectively by freeing them from repetitive manual tasks and allowing them to focus on developing higher-value, more strategic work.

In fact, according to study in the IBM Institute for Business Value study conducted in 2021, the number of CIOs reporting high maturity in AI-enabled workflows increased by 560% compared to the data found in 2019. In the same study, 37% of CIOs surveyed cite process automation as the top opportunity for positive impact within their organizations. In addition, participants indicated that the greatest use of automation is in IT, finance and production.

Another indicator that reflects how companies increasingly value the benefits of the use of AI and automation is the investment being made in these topics. According to a informe presented by International Data Corporation, in November of 2022, the sectors that will invest the most in AI are retail, financial services and manufacturing.

On the other hand, for the incorporation of this new technology in the processes to be sustainable and become part of the competitive advantage of the companies, it also requires an investment in training by the companies and a personal effort of the workers that facilitates the acquisition of new skills, as well as an attitude willing to continuous development and training.

Keepler Data Techcloud data driven partner, continues to highlight the importance of 3 key drivers for the digitization of organizations: process automation, time-to-market reduction and product differentiation. Looking ahead to 2023, Keepler's specialists point out that companies will face 5 short-term challenges:

5 Short-Term Challenges

• Greater data-centric perspective in AI projects prioritizing data quality and consistency. Where correct labeling, data-augmentation strategies, and versioning or feature stores accelerate this process.

• AI projects must take into account privacy and security aspects from their definition, because it is necessary to have more robust and reliable models. In this sense, techniques such as adversarial training help to prevent corrupted data or infrequent scenarios.

• Automation of cognitive processesincorporating services available on different platforms. Cloud (voice, image or text) or making use of pre-trained "multimodal" state-of-the-art models (such as Dall-E or CLIP). Textual (GPT Chat), to solve creative tasks, such as performing semantic synthesis, creating new textual and visual content, or answering questions interactively.

• Increasing Big Data capabilities of increasingly demanding processesWhere quantum computing gains relevance to solve complex problems, perform large-scale simulations or challenges in optimization processes, among others.

• Implement good practices in the form of regulation and commitment so that technology is applied in the most transparent, ethical and fair way possible.

At Dost we remain committed to the efficiency of the resources invested in the invoicing process. We know that there are still some companies that allocate resources for the manual transfer of invoice data to ERP. However, by incorporating Dost in the invoicing process, this step is done automatically, saving time and money.

Contact

For more information, you can contact Dost through our website, LinkedIn, Twitter, Instagram and Facebook.

To contact the Dost team directly, you can send an email to Marta Bigorra, SDR in Dost: mbigorra@mydost.ai mbigorra@mydost.ai