Artificial intelligence for business growth is becoming increasingly acknowledged, and for all the right reasons. Data and artificial intelligence can undoubtedly drive innovation, efficiency, and growth. Some of the reasons for which the technology is being utilised are to automate routine tasks, provide predictive analytics, personalise customer experience, optimise supply chain operations and improve financial and HR processes to name a few.
Also read: Unlocking India’s Economic Potential through Information Technology
Some of the recent reports suggest that 84 percent of the decision makers are excited about artificial intelligence and generative AI. This figure is not surprising, and the meteoric rise displayed by companies such as NVDIA and OpenAI is testimony to it. However, when it comes to the global AI adoption rate it stood at only around 35% in 2022. While this percentage does indicate a steady growth and increase from the previous year, it also states that a lot of industries are yet to realise the potential of data and artificial intelligence.
Why Data and Artificial Intelligence Are Important For Organisations
The US Government and its Public Healthcare system was compelled to undergo a massive data transformation only after the pandemic struck as they were facing immense difficulties with contact tracing, or even in keeping track of their vaccination rates. They had trouble accessing current data because it was in silos.
The COVID-19 pandemic forced states across the US to rethink how to reach the most vulnerable population and prevent the virus from spreading. They needed reliable and current COVID-19 data in order to speed up its response to the pandemic. They also had to go for modernisation of infrastructure to provide quicker actionable data for decision-making because they lacked the infrastructure needed to support their data transformation. The department only underwent this transformation when they were in the eye of the storm.
Challenges Faced by Organisations on Their Data Transformation Journey
Some of the common challenges that organisations face while on their data transformation journey are:
- Limited AI skills, expertise or knowledge.
- The price is too high so they are worried about their ROI.
- Lack of tools or platforms to develop models.
- Projects are too complex or difficult to integrate and scale.
- Organisations siloes and data being in different systems altogether.
- Security and privacy compliance concerns.
- Data complexity.
- Limited number of GPUs.
As organizations navigate these challenges and continue their journey towards data transformation, it is imperative that they prioritize building the necessary skills, investing in robust infrastructure, and fostering a culture of innovation and collaboration. By doing so, they can unlock the full potential of data and artificial intelligence to drive innovation, efficiency, and growth in the years to come.
