Digital transformation was essentially a trend but the pandemic turned it into a necessity for companies regardless of their size. Every company on the planet not only realised the need to embrace digital solutions but also experienced the disruption if they didn’t have a digital strategy in place.
The idea of digital transformation is essentially using 21st century technologies like cloud computing, big data, the internet of things, and artificial intelligence to drive business transformation. With the help of digital transformation, businesses can explore ways to increase flexibility and resilience, lower their cost, improve profitability, customer satisfaction, and even reduce their environmental impact.
One of the trends that took shape but became necessary technology at the same time as digital transformation is artificial intelligence (AI). A number of businesses now feel that when they talk about digital transformation, they are talking about use of AI at the same time. This is primarily because of enterprise AI, which plays a key role in enabling digital transformation. Before we understand the role of AI in digital transformation, let’s see why digital transformation is important.
Importance of Digital Transformation
The fifth edition of the Small and Medium Business Trends report from Salesforce shows that most SMBs survived the pandemic due to digitisation. Organisations around the world are facing the threat of being disrupted by their digitally-equipped competitors. During the pandemic, this theme played out bigger than before with digital tech companies like Amazon not only surviving the pandemic but thriving due to lack of competition.
As people were forced to shelter at home and local shops had to shut their operations, Amazon used its digital technology to not only put more products in front of the eyes of their customers but also successfully delivered them. This digital disruption was also seen in the transformation industry where the likes of Uber managed to move people without any trouble while local taxi drivers struggled to find a fare.
The success of these companies can be owed to their embrace of digital technologies earlier than their peers. According to McKinsey, fewer than 20 per cent of companies have been successful in their digital transformation process. This is not surprising considering the technical and organisational challenges associated with digital transformation.
Another factor benefitting companies like Amazon is their access to massive amounts of current and historical operational data. For every organisation in this post-pandemic world to succeed, they will need to find the key necessary to unlock the value hidden in their data. In order to unlock that hidden value, they need to turn to artificial intelligence and machine learning.
Enterprise AI: what is it and how is it important for digital transformation
Enterprise AI is a category of enterprise software capable of harnessing advanced AI techniques including machine learning, computer vision to drive digital transformation. By deploying enterprise AI applications, organisations are able to see step function improvement in business processes throughout their value chain.
This improvement has often resulted in increased business resilience, greater efficiency, improved profitability, and reduced environmental impact. The new class of enterprise AI applications are being built using the recent innovations in AI and machine learning. Thus, enterprise AI differs from general AI by being focused on high value use cases and deployment at large scale.
An enterprise AI application is embedded into business processes producing meaningful value. The big enterprises are able to develop and operate hundreds of enterprise AI applications to address numerous use cases across their businesses. One good example is Shell using enterprise AI to create AI-driven predictive maintenance applications to monitor the real-time health of more than 5,00,000 valves across its global operations.
Enterprise AI is such a big deal that there is now an entire technology stack being built around it. At GTC 2022, NVIDIA also introduced an updated enterprise AI stack with the intent of becoming a platform player.
The use case of enterprise AI is unlimited and organisations are truly taking advantage by deploying enterprise AI applications across a range of use cases. As mentioned earlier, modern day industry cannot function without predictive maintenance powered by enterprise AI. It is being deployed across maintenance of aircraft, manufacturing equipment, power generation and transmission assets, and oil and gas production equipment (compressors, pumps, valves, etc.)
Enterprise AI is also being used for inventory optimisation, fraud detection, anti-money laundering, securities lending optimisation, and customer retention. Enterprise AI is so vital in digital transformation that we will soon reach a point where every enterprise software application will be AI-enabled.
If small and medium businesses embraced the use of software such as CRM or ERP systems due to the pandemic, these organisations will soon be preparing to adopt AI-enabled versions of these enterprise software. The survival of businesses will eventually boil down to ability to build, deploy, and operate enterprise AI applications at scale.
How AI is being used by companies around the world
At ai.nl, we have taken a look at how AI is transforming the field of healthcare, finance, industry, etc. It is also transforming the order with small and medium enterprises being able to adopt AI technologies at the same pace as their established counterparts. Here is a look at some of the real world use cases of AI driving digital transformation.
- Customer Service: One of the key reasons for companies embracing digital transformation is to drive customer engagement. AI helps solve the hassles associated with response time and with machine learning, companies can deliver pre-emptive service and deliver most of their support online. The technology also frees us human resources to focus on more important work and take more ownership with their conversation with clients.
- Business operations: As mentioned earlier, a number of businesses survived the pandemic by using decision making tools like CRM. IBM estimates this market for data-driven decision-making tools to reach $2T by 2025. For businesses, the real challenge is creating a unified, single source of truth when it comes to data and then making it effectively available for further research and analysis.