AI and digital transformation are converging to create a powerful engine for business growth. Both machine learning (ML) and artificial intelligence (AI) offer the potential to automate processes, enhance decision-making, and create more personalized experiences for customers.

In this article, Silverskills, bolstered by the inputs of its digital transformation experts, will take you through the benefits and challenges of AI and ML for digitalization.

AI and ML: Their Place in Digital Strategy

AI is crucial to many applications of digital transformation. In its absence, the digitization of processes and products would result in vast amounts of data that no human could respond to and analyze within a suitable timeframe.

However, it is important to also view AI through the lens of business possibilities. For instance, according to a report by PwC, AI could contribute as much as $15.7 trillion to the global economy by 2030.

A real-world example of the use of AI would be Amazon, which is using AI to determine which products can be shipped to customers on the same day or the next day.

ML, which itself is a type of AI, is growing ever more in demand in a post-pandemic world that demands faster, more flexible solutions. Indeed, the market size for ML is expected to hit $528.10 billion by 2030.

An example of the use of ML would be Netflix generating variations of high-probability click-through thumbnails.

Benefits of ML and AI in Digital Transformation

The marriage of ML, AI and digital transformation is likely to be a game changer – in many markets, it already is – and there is much value potential for businesses to capitalize on.

• Automating Processes

One of the primary benefits of AI and ML is their ability to automate repetitive and manual processes, such as data entry, customer service, and quality control. By automating these processes, businesses can save time, reduce costs, and improve efficiency.

• Enhancing Planning and Decision-Making

AI and ML can also help businesses make better decisions by analyzing large amounts of data and identifying patterns and trends. This can help businesses optimize their operations, improve product development, and better understand their customers.

For instance, the French multinational manufacturer Danone Group used ML to improve planning and coordination. This led to a 30% reduction in lost sales and a 20% reduction in forecast error.

• Creating Personalized Experiences

ML, AI and digital transformation lend themselves well to creating more personalized experiences for their customers.

For instance, by analyzing customer data, businesses can offer personalized recommendations and promotions, as well as tailored messaging and content.

Sephora, for example, utilizes AI to help customers make more informed purchasing decisions while online shopping. Their Virtual Artist App uses Augmented Reality (AR) to scan the user’s face and enable them to virtually “try on” various makeup products such as lipsticks.

Challenges of AI and ML in Digital Transformation

AI and digital transformation are poised to change the way business is conducted – but the changes come with concerns. Fortunately, there are ways to address them.

• Data Quality

AI and ML rely on high-quality data to make accurate predictions and decisions.

However, many businesses struggle with data quality issues, such as incomplete or inaccurate data, which can negatively impact decision-making, hamper operations, and lead to incorrect analyses.

Some common data quality problems include duplication, inaccuracy, inconsistency, outdated information, irrelevance, and incompleteness.

To address data quality issues, companies require both organizational changes, such as policy compliance and employee training on best practices, as well as technological solutions, such as data management software.

• Technical Complexity and Talent Gap

Implementing AI and ML requires technical skills and infrastructure, which can be challenging for businesses without experience in these areas. This can result in longer implementation timelines and higher costs.

AI and ML are specialized, and need a workforce with an understanding of programming languages, complex algorithms, and data structures.

While there is a disparity between the demand for these skills and the availability of suitable professionals, current employees can be upskilled via intensive training programs. You can also partner with third parties to bridge the gap.

• Ethical Considerations

ML and AI algorithms will only be as unbiased as the data fed into them.

As AI and ML become more widespread, there are growing concerns about their impact on society and ethics. They may inadvertently perpetuate biases and lead to discriminatory or skewed results.

Addressing biases in such technology needs a multifaceted approach, critically examining the data, refining the algorithms, and rethinking the human decision-making involved.

• Data Privacy & Protection

Ultimately, all data is an imprint of human activity and thought. It is no surprise that there is growing concern for data privacy and protection. Indeed, in a survey conducted in the US, 37% of respondents said that they were extremely concerned about online data tracking.

• Regulation and Compliance

As AI and ML become more widely adopted, there is also an increasing need for regulation and compliance. Businesses must ensure that their AI and ML systems comply with data privacy laws, ethical guidelines, and other regulations.

Overall, AI and ML offer significant benefits for digital transformation, but also present significant challenges and risks.

To successfully implement AI and ML, businesses must ensure that they have high-quality data, technical expertise, and a commitment to ethical and regulatory compliance.

By carefully considering these factors, businesses can leverage AI and ML to drive digital transformation and achieve their strategic objectives.

Conclusion

Going forward, more companies will embrace AI and ML in their digital transformation strategy to race ahead of their competitors. We can expect AI/ML to drive exciting products and services – while enhancing rather than replacing the human touch.

However, when deploying new AI/ML systems and models, businesses can struggle with scalability, maintenance, and governance. This is why a robust strategy is key to running successful initiatives that merge ML, AI and digital transformation.

AI and ML are on an upward trajectory in business. But the question is: are businesses equipped with the right talent, technology and mindset to properly utilize them for digitization?

As an IT company specializing in AI/ML software development and advisory, Silverskills can help businesses overcome the challenges of implementing AI and ML for digital transformation. We help businesses with data quality management, technical infrastructure setup, and compliance with regulatory and ethical guidelines.

Silverskills can also provide custom AI/ML software development services tailored to the specific needs of each business.

With a team of experienced AI/ML experts, Silverskills can help you leverage the power of AI and ML to achieve your strategic objectives and drive digital transformation. Contact us now to begin.