From the Internet of Things to predictive analytics to artificial intelligence, a host of cutting-edge technology innovations appear destined to redefine the role of government. Robots, for example, could help governments design better services, while cognitive software applications are already fueling exponential changes in medical research.

But the rate of technological change also raises important questions about the ability of government agencies to adapt. The trend toward "made-for-me" service delivery and citizen-led co-creation is likely to stress the capabilities of many governments, for example. As Jack Welch, then CEO of GE, famously said, "If the rate of change on the outside exceeds the rate of change on the inside, the end is near."

To be sure, a whole new economy of problem-solvers -- what in our book we call "the solution economy" -- has emerged to tackle some of our toughest societal challenges. This means governments won't have to go it alone. These wavemakers, however, can't change the basic operating systems of government. That responsibility lies within government itself.

The good news is that there are lots of perspectives on the opportunities presented by rapid advances in technology. Deloitte's Gov2020 research, for example, highlights almost 200 trends that could shape the future of governments.

How government bodies evolve and adapt matters to us all. And in a world of exponential change -- where we have the potential to move more people out of poverty than ever before, to arrest or eradicate terrible disease, and to reverse the threat of global warming -- the potential benefits of governments that are capable of continuous adaptation, based on applied learning, has never been greater.

But can our governments adapt to an age of exponential change? Could there be such a thing as a "cognitive government," one that is itself a learning system that adapts in concert with others? What would it look like? How would it be achieved?

The secrets to achieving a cognitive government are likely to come mainly from within. That is, only those who have the authority and accountability to change the system can really do so.

So who will or should lead this change? Most government leaders' authority and accountably extends to only a relatively small part of the overall bureaucracy, severely limiting the influence they can have. They do not command the complete architecture of government. That's why a philosophy that views governments as cognitive enterprises capable of learning and adapting in a highly networked system could signal a fundamental breakthrough in public management.

But first, serious work needs to be done on what a government entity reinvented as a learning system would resemble and how it would operate. We believe that creating cognitive government involves at least three core elements:

Open functionality. The public sector needs to evolve from open government and open data to co-creation by better tapping into collective intelligence. Governments should do more than just opening up; they need to become parts of co-creation ecosystems.

Applied learning. Governments must become more nimble in their ability to sense and respond. The aptitude to prototype, rapidly iterate, and fail well and fail fast should become core tenets of nearly every project rollout. Agile, lean, user-centric and design-thinking approaches must be core methodologies of these governments.

Adaptive rule-making. In his book "The Rule of Nobody," Phillip Howard ably documents how bureaucracy, regulations and dead laws tie public-sector leaders' hands and lead to sclerotic government. Fixing the problem requires understanding and changing the rules that define the architecture of government and limit its ability to scale innovations. Examples include rules related to data sharing, organizational design and job descriptions, hiring and firing, and contracting.

The past decade or two offers some lessons in how to get from here to there. Many governments have been successful in creating e-government services. Evolving these to a "mobile-first" delivery system is a natural step. But the Internet of Things is rapidly changing many business models and presents near-limitless opportunities to improve our daily lives. How can governments shorten the learning curve to more effectively adapt to the technological changes that surround them?

Excitement (and concern) is building around the potential of rapid advancements in artificial intelligence, cognitive systems and machine-to-machine learning. But for society to benefit from the true power of these and other technologies, our institutions will also need to become more adaptive. We can achieve more than innovation around the edges of our public agencies.