At the intersection of analytics and smart technology, companies are starting to see the long-awaited benefits of AI.

After years of hope and promise, 2018 may be the year when artificial intelligence (AI) gains meaningful traction within Fortune 1000 corporations. This is a key finding of NewVantage Partners’ annual executive survey, first published in 2012. The 2018 survey, published on January 8, represented nearly 60 Fortune 1000 or industry-leading companies, with 93.1% of survey respondents identifying themselves as C-level executive decision-makers. Among the 2018 survey participants were corporate bellwether companies, including American Express, Capital One, Ford Motors, Goldman Sachs, MetLife, Morgan Stanley, and Verizon.

The main finding of the 2018 survey is that an overwhelming 97.2% of executives report that their companies are investing in building or launching big data and AI initiatives. Among surveyed executives, a growing consensus is emerging that AI and big data initiatives are becoming closely intertwined, with 76.5% of executives indicating that the proliferation and greater availability of data is empowering AI and cognitive initiatives within their organizations.

The survey results make clear that executives now see a direct correlation between big data capabilities and AI initiatives. For the first time, large corporations report that they have direct access to meaningful volumes and sources of data that can feed AI algorithms to detect patterns and understand behaviors. No longer dependent on subsets of data to conduct analyses, these companies combine big data, AI algorithms, and computing power to produce a range of business benefits from real-time consumer credit approval to new product offers. Companies such as American Express and Morgan Stanley have publicly shared stories of their successes within the past year.

Staving Off Disruption

Survey participants comprised executives representing data-intensive industries, notably financial services companies, which constituted 77.2% of the survey respondents. Financial services companies have long been at the forefront of industry due to the large volumes of transactional and customer data that they maintain, and they have developed robust data management and data governance processes over a period of decades. These organizations have been at the forefront in the use of analytics to manage risk, assess customer profitability, and identify target market segments. Industries such as life sciences, while newer to data management, possess vast repositories of scientific and patient data that have gone largely untapped relative to the potential for insight.

Now, many of these mainstream companies are facing threats from data-driven competitors that have no legacy processes and have built highly agile data cultures. Companies like Amazon, Google, Facebook, and Apple are among the most prominent disruptive threats to these traditional industry leaders. As mainstream companies increase their investment in big data and AI initiatives, they face a range of issues and challenges as they seek to organize to compete against data-driven competitors. This concern is highlighted in the 2018 survey results.

A clear majority (79.4%) of executives report that they fear the threat of disruption and potential displacement from these advancing competitors. In response to the threat of disruption, companies are increasing their investment in big data and AI initiatives. In the 2018 survey, 71.8% of executives indicate that investments in AI will have the greatest impact on their ability to stave off disruption (in the next decade). Although overall investments in AI and big data initiatives continue to be relatively modest for most large corporations, 12.7% of executives report that they have invested half a billion dollars in these initiatives to date. If the fear of disruption is any indication, this number can be expected to increase.

Driving Innovation Through AI

Executives indicate that investments in big data and AI are beginning to yield meaningful results. Nearly three-fourths of executives surveyed (73.2%) report that their organizations are now achieving measurable results from their big data and AI investments. In particular, executives report notable successes in initiatives to improve decision-making through advanced analytics — with a 69% success rate — and through expense reduction, with a 60.9% success rate. Businesses are also using big data and AI investments to accelerate time-to-market for new products and services (54.1% success rate) and to improve customer service (53.4% success rate). Yet, just over one-fourth (27.3%) of executives report success thus far in monetizing their big data and AI investments. This remains an elusive goal for most organizations.

Nearly one-fourth (23.9%) of respondents report that their investments in big data and AI are highly transformational and innovative for their organization, and potentially disruptive for their industry. But 43.8% of executives report that innovation and disruption initiatives involving big data and AI yield successful results for their organizations.

As mainstream companies look to the future, there is a growing consensus that AI holds the key. With 93% of executives identifying artificial intelligence as the disruptive technology their company is investing in for the future, there appears to be common agreement that companies must leverage cognitive technologies to compete in an increasingly disruptive period. Investment in AI can be expected to increase as organizations position themselves to compete in the future. Those companies that prove themselves to be adept at developing and executing initiatives using big data and AI capabilities will likely be the companies that are best positioned to deflect the threats of agile, data-driven competitors in the decade ahead.

5 Comments On: How Big Data and AI Are Driving Business Innovation in 2018

  • Alexa Jones | February 27, 2018

    This is actually true. Big Data and Artificial Intelligence is the future of digitalisation. Big companies have already made huge inroads in data analysing and storing. The growth from Web Designing to high level technologies like Hadoop is mindblowing.

  • Sanjay Singhvi | March 6, 2018

    Success of AI in any organization dependent on the quality of data available and to ensure rich data source big data and master data management is key. One of the key factor for AI to succeed is availability of accurate data for at least three to five years.

  • Rhys Gambling | June 10, 2018

    An interesting article but the topic of digitization is a vast topic area of major importance. It is in my view the result of the combined learning of the human race the past years which has led to commodification of technology which is why we are where we are now. More importantly, I believe it is time to use these technologies for the good of all. None of the existing political systems really function well and our current outlook based on this and population growth is not sustainable. Companies need to start thinking in the medium to long term instead of just short term wins. The barriers to entry are down as per Porters 5 forces and society is on the change. The buy my way back in to the market approach used by so many incumbents of the past is failing. The new kids on the block have taken the risk and are making the gains. AI, big data, is a tiny part of digitization but is also important. Great strides can be made where everyone benefits but the though process in society needs to change. Enter a new concept called “sharing”. No it’s not a joke but a change in mindset. The bigger question is, can we rise to challenge and be progressive in our outlook. Adaptability is key in my view!

  • Subodh Saxena | June 15, 2018

    Unlike humans, AI in its present form needs big data for meaningful results and is not able to use the experience for another similar application. The work in progress on more effective Deep Learning is likely to overcome these limitations to some extent in near future. In such a scenario dependence on big data may be reduced and AI driving business innovation will be smoother.

  • Martin Carroll | October 26, 2019

    This is a nice article and I’m fascinated by the comment that, ‘Yet, just over one-fourth (27.3%) of executives report success thus far in monetizing their big data and AI investments. This remains an elusive goal for most organizations.’

    I’d like to understand the definition of monetization in the study this article describes. Particularly to the extent that it is different to the other forms or categories of objectives measured. Can anyone comment? I have read the report itself and it is not clear, see objectives 1-6 below.

    I presume it is more to do with using a company’s data as a ‘product’, or service, in and of itself. That is, not for operating their own business per se, but for other adjacent players in the ecosystem or supply chain to achieve benefits 1-5 below.

    Top objective of Big Data and AI investments
    – 1 Advanced analytics/better decisions
    – 2 Improve customer service
    – 3 Decrease expenses
    – 4 Innovation/disruption
    – 5 Speed to market
    – 6 Monetization

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