It’s become inevitable in IT. Something new appears on the horizon and the hype machine ramps up to warp speed as it drafts a new term into its sales and marketing patter. In some cases, companies relabel their existing wares to align with the new term without making any actual change to the product.
Sometimes the hype is justified, often it is not. How about artificial intelligence (AI) and machine learning (ML)? Gartner believes they are over-hyped according to its recent Gartner Magic Quadrant for Data Science and Machine-Learning Platforms.
Case in point: a recent interview with a software vendor led to the confession that the “AI capabilities” spoken about in their brochures weren’t there yet. In other words, they were taking advantage of the hype to get more eyes viewing their software.
Gartner doesn’t dismiss AI and ML as being without wholly substance. In fact, it goes on to name the top 20 candidates, explaining their strengths and weaknesses. These platforms are already proving valuable to data scientists and analysts in sourcing data, constructing models, analyzing data, and spotting trends. That value is translating into sales. Gartner reports heavier investment in AI during the COVID-19 pandemic. The analyst firm’s best advice on how to see beyond the glowing marketing promises is to tightly focus ML and AI into actual use cases that deliver tangible business value.
Read more on COVID-19’s impact on IT spending patterns.
And IT has to be cognizant of how the hype may be influencing top management. CEOs and board room members are being assailed on all sides by the wonders of this or that AI platform. This may cause them to demand the replacement of existing analytics and business intelligence tools at once!
Before going all in…
Calm heads must prevail for a number of reasons. Here are five to keep in mind.
Changing platforms may be expensive and may not add that much functionality or value.
Your existing vendor may offer add any missing features at a fraction of the cost and on a timeline you dictate. You never know until you ask.
The new functions drooled after by top management may sound good. But will they add much value to the bottom line? And will the new platform alter ongoing and successful organizational sales processes?
Does any proposed new platform integrate well with existing cloud platforms and BI tools?
Are users being considered? All too often, management buys into features that make their lives easier such as enhanced reporting. One example from many years ago: a new post office was loved by management and hated by front line workers as it actually slowed their ability to complete transactions.
Choosing the Right AI and ML Tools
If real value can be gained, push ahead with AI and ML investments. Gartner noted that the market generated $4 billion in 2019 and is growing at 17% per year. But not all tools are the same. Some platforms are focused on the data scientist and require highly trained personnel. A few can afford such personnel, but many can’t. Other tools aim to democratize AI and ML. That may work for some organizations and not others.
Gartner listed the usual suspects as its leaders in the Magic Quadrant such as long time BI pioneers SAS, IBM Watson, and MathWorks. SAS Visual Data Mining and Machine Learning currently rules the roost, according to Gartner, with the two others not far behind.
But beware the incursion from the cloud giants Google, Microsoft, and Amazon. The latter was late to the party and is now coming on strong. There are also a lot of others competing in a crowded market. Those earning high markets from Gartner include Dataiku, Databricks, Tibco, Alteryx, DataRobot, KNIME, RapidMiner, and H2O.ai.
The question remains: Will SAS, IBM, and MathWorks be able to maintain their grip on the market? Or will they be overwhelmed by the cloud brigade? Amazon SageMaker is making a big play right now and is gaining major traction. Not to be outdone, the launch of a unified AI platform from Google is imminent.
Regardless of the hype, this market is primed for major growth in the coming years. Those who win will be those who see through the marketing blitz to direct AI and ML initiatives towards the attainment of strategic business objectives.
Source: https://www.cioinsight.com/innovation/ai-machine-learning-substance-behind-the-hype/
