In my last blog on data governance gaps and the challenges it poses to AI modernization in the public sector, I wanted to turn the tables and discuss what the private sector could do to help close the AI knowledge and skill gaps in government. The World Economic Forum (WEF) report highlighted five key roadblocks impacting the public sector on advancing data in relationship to AI practices which include:

  1. Many public sector and government organizations have an elementary understanding of their data.
  2. Employees often do not possess the necessary AI and data management skills.
  3. The AI landscape is becoming increasingly complex and competitive.
  4. There is less encouragement for public sector employees to be innovative and take risks.
  5. AI algorithms require upkeep from the specific providers, which is an added cost for public sector organizations.

Public Sector Strategies for Supporting Government Modernization in AI

According to EY, artificial intelligence can help government automate repetitive tasks, and make better decisions to improve customer experience. This is true for all sectors. Governments using AI have an incredible opportunity to transform how they are working and operating their processes.

Citizens want efficient services and unified views of their data, and being able to share data across government functions, without putting at risk citizen privacy.

EY has stated that: AI offers governments two big opportunities that don’t apply to the private sector:

  1. It allows them to structure and analyze the huge amount of data they hold on citizens – and use it for social good. This means they can quantify and reduce inequalities in outcomes as well as opportunities. They can also share the data with third parties, who can create apps or services that improve life for citizens, while making sure those parties keep the data private.
  2. It also gives them a unique chance to drive how citizens use and benefit from these technologies. That’s because governments are also responsible for role-modelling the ethical use of AI, regulating how companies apply it and educating citizens to be ready for its challenges.

With this background, here are five strategies that the public sector could consider to action to accelerate government’s effectiveness and efficiency in advancing AI practices.

Strategy One Bring More Strategic Value

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Evaluate what percentage of revenue in your companies is focused on the government industry, and if it is high, then add more strategic value to your account teams servicing your government customers. For example, if you are a tier one bank, like my alma matta, Citicorp, or a tier one telecom, like Bell Canada, or a high tech leader, like Amazon, Google, Microsoft, Salesforce,… why not have your Chief Data Scientist of Chief AI officer join your Sales Account Executive Team and do a current state knowledge sharing of where your government customers are on on their AI journey vs your organization. This could be an MBA or Masters of AI in a unique employee onboarding/culture integration training program supporting your senior leaders as documentation needs will be high to keep the learnings moving along. Even if you are not selling AI related services, your private organizations have learned so much that you can set up best practice knowledge sharing sessions, create an integrated innovation lab to help build new skills in your government clients. In other words, bring more value to your government accounts in helping them design and build out their AI skills and competencies with your guidance and wisdom as you are likely much further ahead in your own AI maturity continuum.

Strategy Two – Think of Government as an Investment for Corporate Purpose and Society Betterment

Think of your government organizations as charities and allocate a percentage of your global revenues into focused AI programs to help modernize data governance – to help set up machine learning operations infrastructure and also centralize data sources as access to data is so key to AI initiatives. We need to invest more in our public sector and increasing taxes is not the answer as it is no incentive for the private sector or citizens to help more.

Strategy Three – Set up Shared Services for your AI functions internally and invite your key government customers to join in your shared services infrastructure operations, in other words, start adopting and enabling more support for your public institutions.

Strategy Four – Collaborate on AI, and Data Training Know-How

When you invest in Training for AI for your Talent – invite your customers in the government to join you. They often don’t have the operating training budget dollars that the private sector does, so as in strategy one – find ways to bring more value forward and share your knowledge more.

Strategy Five – Work with your government leaders to help them design their organizations of the future by ensuring they know your business needs so they can learn more rapidly about You to service your needs more – and vice versa, for you to understand their operating challenges. Create advisory ambassadors so your younger employees can make valuable contributions to society in voluntary projects. These government projects can be identified so your employees can easily lend a helping hand. I bet if you posted a job description for one day a week for a senior AI engineer or data scientist to work in one of your largest government customers, without impacting their pay – many of your employees would jump at the opportunity – as your people care about making our world a better place.

Conclusion:

These are just five strategies that the private sector can think about to support the public sector. There are many associations that are available for knowledge sharing in these two sectors, but its the sustaining knowledge flow that makes a valuable contribution to modernization needs. As has been well proven, very few investments in conferences or even in educational settings have a Return on Investment, unless what one learns has an immediate traction or execution opportunity to apply the knowledge acquired.

We do have some major gaps in our public sector in data modernization and AI data governance. The issues outlined by the World Economic Forum are only a few of the issues that characterize many public institutions. What we must internalize is how fast China is evolving in its strength of centralizing data and connecting all ecosystems into intelligent hubs of “AI everything.” As the USA National Security Commission wrote in their reports earlier this year, China is a national security threat in AI, and in Canada this also holds true.

The question is a big one – As board directors and C-Suite Leaders, what are your plans to close this gap that is only widening as each day passes.

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