Constellation Research analysts outlined a series of predictions for the years ahead at Constellation Research Connected Enterprise 2023.

CEO Ray Wang was moderating an early panel at CCE with our merry band of analysts about predictions. He was put on the spot and asked about ERP in the next 10 years. Wang's reply: "It'll still be here."

His other takeaway is that a mentor once told him that predicting the future is possible if you go back 30 to 50 years, examine what happened and change names around.

With all those caveats in mind, here are a few of trends to ponder.

Doug Henschen:

  • Leading enterprises are consolidating data in lakehouses and data fabrics that are far more flexible than the data warehouses of yore. That move will be a necessary step to making use of all your data—structured, semi-structured, unstructured—to drive AI. 
  • Boundaries between analytics/BI and predictive data science are already eroding. As we move into GenAI, those boundaries will disappear. We’ll want to ask, “what happened, why did it happen, what’s next and what should we do about it?”

Dion Hinchcliffe:

  • Boards are seeking AI impact immediately, pressuring CIOs.
  • AI transformation of work a big focus area.
  • Generative AI is just the beginning of AI revolution.
  • Transformative AI solutions to drive growth are the end-game.

Liz Miller:

  • The roadmap for use of gen AI for improving employee and customer experience is not well defined.
  • The creator economy is here, and businesses are not ready.
  • There's too much data and not enough strategy to drive experience.

Holger Mueller:

  • We are in the era of infinite computing.
  • The availability of computing is no longer a constraint. LLMs are really LKMs (knowledge models) or need to become LKMs.

Andy Thurai:

  • The possibilities for AI are boundless.
  • Business leaders are excited about AI.
  • Those business leaders are also freaked out about AI use cases.

Steve Wilson:

  • A big progressive vision for data protection is emerging.
  • There's an urgent need to get the data you need in real time at the edge.
  • The quality of metadata to tell you if it’s true.
  • Safety to data infrastructure needs to be taken seriously. It's like clean drinking water.

My time frame is a bit shorter but here are a few working theories for the next 12 months and change.

  • Generative AI in enterprise moves from productivity to more growth, transformation.
  • There will be vendor consolidation. Enterprises were doing it, but M&A will pick up.
  • Automation will move beyond low hanging fruit. What are pitfalls?
  • Few enterprises have their data games down. As result we GenAI backlash because it's highly unlikely that enterprises will acknowledge they don't have their data acts together.
  • Smaller vendors may be in trouble. IT spending reflection of S&P 500, customers are consolidating vendors and a lot of debt will be refinanced.