AI Implementations Lag Expectations

Audio version of the article

Is there a lag between enthusiasm for investment in Artificial Intelligence (AI) capabilities and delivery of AI results?  Apparently so.   A 2019 Harvard Business Review article, Building the AI-Powered Organization, notes “Artificial intelligence is reshaping business – though not at the blistering pace many assume”. The HBR article concludes, “Despite the promise of AI, many organizations’ efforts are falling short”. 

The Wall Street Journal echoed this perception in a story quoting newly-appointed IBM CEO Arvind Krishna, Data Challenges Are Halting AI Projects, IBM Executive Says. According to Krishna, “Data related challenges are a top reason why IBM clients have halted or cancelled artificial-intelligence projects. The cost and hassle of collecting and preparing data comes as a shock for some companies”. 

So, what is the current state of corporate AI investment and business results?  Having recently surveyed top executives of nearly 75 leading firms, and written about examples of AI rollouts at firms including JPMorganChaseCapital One, and TD Ameritrade, it is our view that the current state of AI can be summarized succinctly. Leading companies are investing heavily in AI capabilities, but roll-out remains gradual.  For the most part, companies are embracing AI with commitment but caution.  For many firms, implementations are lagging expectations. 

Among the principle findings of our 2020 executive survey:

1.   AI investment is up, but the pace of investment may be easing

The percentage of firms investing greater than $50MM in AI and data capabilities is up to 64.8% in 2020 from just 39.7% in 2018, with a total of 98.8% of firms making investments in these initiatives. However, there are signs that the pace of investment may be leveling off. While 91.6% of executives reported that Big Data and AI investments were accelerating in 2019, nearly half – 46.9% — of those executives now report that these investments are now being undertaken at a steadier pace. 

What is noteworthy is the degree to which the urgency associated with last year’s investments in these initiatives appears to have eased.   This may be a case of companies digesting those investments they have already made, or a case of taking a wait and see attitude to see whether these investments demonstrate measurable results.

2.   AI implementations remain early, but most firms are experimenting

Reinforcing this perspective, firms report an ongoing level of robust interest and an active embrace of AI technologies and solutions, with 91.5% of firms reporting ongoing investment in AI. 

AI Implementations Lag Expectations 2

However, deployment of AI capabilities and solutions remains at an early stage. While only 14.6% of firms report that they have deployed AI capabilities into widespread production, most firms – 65.8% — report that AI is now in some form of initial production, and an overwhelming 92.6% of firms report that AI initiatives are underway in some form. 

AI Implementations Lag Expectations 3

3.   AI continues to be viewed as the most disruptive emerging technology

AI and Machine Learning continue to be viewed as the most disruptive technology, although the percentage of firms naming AI/Machine Learning has decreased from 80.0% in 2019 to 69.5% in 2020. In recent years, AI has jumped from being named as most disruptive technology from just 46.6% of 2017 to its present level, with Cloud Computing a distant second choice at just 11.0%. 

AI Implementations Lag Expectations 4

4.   Adoption remains a challenge, as firms cite cultural obstacles

As has been the case over the past several years, adoption of disruptive technologies continues to represent a challenge for most companies, with 73.4% reporting an ongoing adoption challenge, and 90.9% citing cultural issues, including people and process, as the principal obstacles.

AI Implementations Lag Expectations 5

5.   Companies struggle to become data-driven

It has been noted that issues of data quality and data access remain a barrier to AI execution, as highlighted by IBM’s Krishna. Organizations continues to struggle with issues of data management, and only 37.8% offirms report that they have created a data-driven organization. 

AI Implementations Lag Expectations 6

In the Foreword to our 2020 survey, co-authored with Thomas H. Davenport, author of the seminal work Competing on Analytics, we note that companies are “struggling to succeed despite massive investments in technology and applications”.  While the promise of AI remains strong, organizations must focus on issues of execution and adoption if they expect to see transformative business results from their AI investments. Among those companies that were surveyed, the challenges that loom largest are driven by people and process obstacles, not technology barriers. These human issues can and must be addressed for organizations to move forward successfully. 

In sum, we believe that those companies that adapt in a “in a more human direction” will be best positioned to take advantage of and leverage investments in AI capabilities for the future. We conclude, “While human change is almost always more difficult to accomplish than technical change, it is hardly impossible”.   

This article has been published from a wire agency feed without modifications to the text. Only the headline has been changed.

Source link

- Advertisment -AI Implementations Lag Expectations 8AI Implementations Lag Expectations 9

Most Popular

- Advertisment -AI Implementations Lag Expectations 10AI Implementations Lag Expectations 11