Avoiding The Same Mistakes

Many companies jump into AI without considering what they really need is a systemic approach to the use of AI before trying to use AI. The emphasis needs to focus on transformation and improving AI maturity, not just one-off projects. AI maturity requires a continuous education plan about AI and a roadmap to long-term AI transformation.

The roadmap needs to address potential organizational changes required to optimize the use of AI systemically. For instance, many organizations have failed to collect and use data from a scientific standpoint. Data is the gold of the 21st Century but most organizations do not know how to organize their data for effective use by AI.

We have witnessed a massive transformation in the volume, variety, and velocity of data available, both on-premises and increasingly in cloud environments. This requires organizations to have a comprehensive data integration and management strategy which would include a training and education plan as to using and managing data effectively. However, organizations are largely still applying “microwave solutions without knowing individual and organizational needs”. Too many firms send their people to take online courses on AI subject matters without understanding the subject matter, to begin with. More and more the evidence suggests a ready, fire, aim mentality.

Back to the Future

As we move further into the 21st Century technology will continue to transform the business landscape yet the barriers to change will remain the same. These barriers are the crucibles of progress for organizations, industries, and societies at large.

A survey conducted by the Artificial Intelligence World Conference listed several changes needed for AI success within the government and the private sector. The critical changes needed are in the areas of workforce training, data, and culture.

Improved data governance, data-centric architecture, and increased consistency of data formats and tagging were the top three needs in terms of data. This is also the area where survey respondents expect the quickest returns: 77% expect better data analytics to be the top AI mission outcome.

Workforce needs are also significant, mainly centered on staff. Increased training for our current workforces in data science and AI, the survey found, as well as increased hiring of AI-specific subject matter experts, the respondents said. And on the process side, survey respondents requested formal processes and methods to guide AI implementation.

Finally, the survey respondents identified needs in company culture. Senior management needs a more data-driven strategic vision around AI, they said, and culture must shift to value data across all functions. They would like to see a commitment to data-driven decision making across government and enterprise.

It appears the faster things change the more things remain the same. Whether the target is to improve quality or adopting the latest technology, the consistent restraint to progress is understanding and using data and cultural transformation. To truly overcome these restraints leaders must slow down and learn to overcome the constraints and accelerate the transformation. The alternative is to simply go back to the future.

As the great historian George Santayana said: “Those who cannot remember the past are condemned to repeat it." I think there is an AI algorithm that can help leaders remember the past. What say you?