Financial services companies demonstrate high level of AI maturity, says LXT report
07 April 2022 US
Image: adobestock/putilov_denis
A report by LXT, the US-based specialist in AI training data, has found that US financial services companies are currently demonstrating high levels of artificial intelligence (AI) maturity.
The report, titled: ‘The Path to AI Maturity’, asked 200 senior US decision-makers their opinions on the factors that are driving firms towards this maturity. The results of this survey can be used to infer what makes an organisation AI mature, so that other organisations can follow in their path, says LXT.
The Gartner AI maturity model provides a measure of the maturity level of AI projects adopted by participating companies. The model identifies five levels of AI maturity are, from lowest to highest: awareness, active, operational, systematic, and transformational.
The Gartner model aims to provide objective insight into how organisations judge the sophistication of their own AI implementations. The organisations surveyed were asked to select the level of AI maturity for their organisation from one of the five Gartner AI maturity model levels.
According to the report, dedicating an overall higher budget to AI programmes may be the right step for organisations seeking greater AI maturity. On the maturity model, companies in the systematic and transformational levels are budgeting higher amounts overall for their AI programmes.
This is empowering, according to LXT, as it highlights a relationship between AI success and allocation of investment. This presents a clear path for businesses looking to get ahead in the AI race.
LXT adds that leaning towards more supervised machine learning can increase AI maturity. Companies focusing on supervised and semi-supervised machine learning approaches were at the systematic and transformational levels, while those at the awareness level were generally found to lean towards unsupervised machine learning.
The survey results show that companies moving through the phases of AI maturity, at a point where AI is successfully in production, place an increased value on quality training data.
Systemic and transformational organisations say that quality training data is the most important contributor to the success of AI strategies, ahead of quality controls and good algorithms. Consequently, companies at the highest levels of maturity indicate the strongest need to increase their training data budgets over the next five years.
LXT finds that the financial services industry reported the highest levels of AI maturity across the business sectors surveyed, having adopted AI at an early stage to maintain competitive advantage in the market.
The rise in customer demand for digital experiences has led financial services institutions to embrace AI, the report adds. This is viewed by many firms surveyed as a powerful tool to transform their businesses, from internal operations to customer engagement.
The report, titled: ‘The Path to AI Maturity’, asked 200 senior US decision-makers their opinions on the factors that are driving firms towards this maturity. The results of this survey can be used to infer what makes an organisation AI mature, so that other organisations can follow in their path, says LXT.
The Gartner AI maturity model provides a measure of the maturity level of AI projects adopted by participating companies. The model identifies five levels of AI maturity are, from lowest to highest: awareness, active, operational, systematic, and transformational.
The Gartner model aims to provide objective insight into how organisations judge the sophistication of their own AI implementations. The organisations surveyed were asked to select the level of AI maturity for their organisation from one of the five Gartner AI maturity model levels.
According to the report, dedicating an overall higher budget to AI programmes may be the right step for organisations seeking greater AI maturity. On the maturity model, companies in the systematic and transformational levels are budgeting higher amounts overall for their AI programmes.
This is empowering, according to LXT, as it highlights a relationship between AI success and allocation of investment. This presents a clear path for businesses looking to get ahead in the AI race.
LXT adds that leaning towards more supervised machine learning can increase AI maturity. Companies focusing on supervised and semi-supervised machine learning approaches were at the systematic and transformational levels, while those at the awareness level were generally found to lean towards unsupervised machine learning.
The survey results show that companies moving through the phases of AI maturity, at a point where AI is successfully in production, place an increased value on quality training data.
Systemic and transformational organisations say that quality training data is the most important contributor to the success of AI strategies, ahead of quality controls and good algorithms. Consequently, companies at the highest levels of maturity indicate the strongest need to increase their training data budgets over the next five years.
LXT finds that the financial services industry reported the highest levels of AI maturity across the business sectors surveyed, having adopted AI at an early stage to maintain competitive advantage in the market.
The rise in customer demand for digital experiences has led financial services institutions to embrace AI, the report adds. This is viewed by many firms surveyed as a powerful tool to transform their businesses, from internal operations to customer engagement.
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